Maleike, D.a , Nolden, M.a , Meinzer, H.-P.a , Wolf, I.a b
Interactive segmentation framework of the Medical Imaging Interaction Toolkit
(2009) Computer Methods and Programs in Biomedicine, 96 (1), pp. 72-83.
a German Cancer Research Center, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany
b Mannheim University of Applied Sciences, Paul-Wittsack-Straße 10, 68163 Mannheim, Germany
Abstract
Interactive methods are indispensable for real world applications of segmentation in medicine, at least to allow for convenient and fast verification and correction of automated techniques. Besides traditional interactive tasks such as adding or removing parts of a segmentation, adjustment of contours or the placement of seed points, the relatively recent Graph Cut and Random Walker segmentation methods demonstrate an interest in advanced interactive strategies for segmentation. Though the value of toolkits and extensible applications is generally accepted for the development of new segmentation algorithms, the topic of interactive segmentation applications is rarely addressed by current toolkits and applications. In this paper, we present the extension of the Medical Imaging Interaction Toolkit (MITK) with a framework for the development of interactive applications for image segmentation. The framework provides a clear structure for the development of new applications and offers a plugin mechanism to easily extend existing applications with additional segmentation tools. In addition, the framework supports shape-based interpolation and multi-level undo/redo of modifications to binary images. To demonstrate the value of the framework, we also present a free, open-source application named InteractiveSegmentation for manual segmentation of medical images (including 3D+t), which is built based on the extended MITK framework. The application includes several features to effectively support manual segmentation, which are not found in comparable freely available applications. InteractiveSegmentation is fully developed and successfully and regularly used in several projects. Using the plugin mechanism, the application enables developers of new algorithms to begin algorithmic work more quickly. © 2009 Elsevier Ireland Ltd. All rights reserved.
Author Keywords
Application; Framework; Interaction; Segmentation
Document Type: Article
Source: Scopus
Withey, D.J.a , Pedrycz, W.b , Koles, Z.J.b c
Dynamic edge tracing: Boundary identification in medical images
(2009) Computer Vision and Image Understanding, 113 (10), pp. 1039-1052.
a Department of Engineering Technology, Northwestern State University of Louisiana, Natchitoches, LA 71497, United States
b Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alta., Canada
c Department of Biomedical Engineering, University of Alberta, Edmonton, Alta., Canada
Abstract
Medical image segmentation is a sufficiently complex problem that no single strategy has proven to be completely effective. Historically, region growing, clustering, and edge tracing have been used and while significant steps have been made in the first two, research into automatic, recursive, boundary following has not kept pace. A new, advanced, edge-tracing algorithm capable of combining edge, region, and pixel-classification information, and suitable for magnetic resonance image analysis, is described. The algorithm is inspired by automatic target tracking, as used in civilian and military aerospace operations. Comparison with clustering and level sets is performed. Results indicate that no method is uniformly superior, that the new algorithm provides information not available from the other approaches, and that it can utilize a variety of sources including results from other methods. The algorithm is applied to two-dimensional slice images and extension to three-dimensional images is discussed. © 2009 Elsevier Inc. All rights reserved.
Author Keywords
Edge tracing; Image segmentation; Kalman filter; Magnetic resonance imaging; Medical image analysis; Target tracking
Document Type: Article
Source: Scopus
Ullner, P.M.a , Di Nardo, A.d , Goldman, J.E.b , Schobel, S.c , Yang, H.a , Engelstad, K.a , Wang, D.a , Sahin, M.d , De Vivo, D.C.a
Murine Glut-1 transporter haploinsufficiency: Postnatal deceleration of brain weight and reactive astrocytosis
(2009) Neurobiology of Disease, 36 (1), pp. 60-69.
a Department of Neurology, Colleen Giblin Laboratories for Pediatric Neurology Research, Columbia University, New York, NY, United States
b Department of Pathology, Columbia University, New York, NY, United States
c Department of Psychiatry, Columbia University, New York, NY, United States
d Department of Neurology, Children's Hospital, Harvard Medical School, Boston, MA, United States
Abstract
Glucose transporter type 1 (Glut-1) facilitates glucose flux across the blood-brain-barrier. In humans, Glut-1 deficiency causes acquired microcephaly, seizures and ataxia, which are recapitulated in our Glut-1 haploinsufficient mouse model. Postnatal brain weight deceleration and development of reactive astrogliosis were significant by P21 in Glut-1+/- mice. The brain weight differences remained constant after P21 whereas the reactive astrocytosis continued to increase and peaked at P90. Brain immunoblots showed increased phospho-mTOR and decreased phospho-GSK3-β by P14. After fasting, the mature Glut-1+/- females showed a trend towards elevated phospho-GSK3-β, a possible neuroprotective response. Lithium chloride treatment of human skin fibroblasts from control and Glut-1 DS patients produced a 45% increase in glucose uptake. Brain imaging of mature Glut-1+/- mice revealed a significantly decreased hippocampal volume. These subtle immunochemical changes reflect chronic nutrient deficiency during brain development and represent the experimental correlates to the human neurological phenotype associated with Glut-1 DS. © 2009 Elsevier Inc. All rights reserved.
Author Keywords
Apoptosis; Astrogliosis; Brain development; Fasting; Glut-1 deficiency mouse model; GSK3-β; Lithium; Microcephaly; mTOR; Proliferation
Document Type: Article
Source: Scopus
Babalola, K.O., Patenaude, B., Aljabar, P., Schnabel, J., Kennedy, D., Crum, W., Smith, S., Cootes, T., Jenkinson, M., Rueckert, D.
An evaluation of four automatic methods of segmenting the subcortical structures in the brain
(2009) NeuroImage, 47 (4), pp. 1435-1447.
University of Manchester, Imaging Science and Biomedical Engineering, Stopford Building, Oxford Road, Manchester, M13 9PT, United Kingdom
Abstract
The automation of segmentation of subcortical structures in the brain is an active research area. We have comprehensively evaluated four novel methods of fully automated segmentation of subcortical structures using volumetric, spatial overlap and distance-based measures. Two methods are atlas-based - classifier fusion and labelling (CFL) and expectation-maximisation segmentation using a brain atlas (EMS), and two incorporate statistical models of shape and appearance - profile active appearance models (PAM) and Bayesian appearance models (BAM). Each method was applied to the segmentation of 18 subcortical structures in 270 subjects from a diverse pool varying in age, disease, sex and image acquisition parameters. Our results showed that all four methods perform on par with recently published methods. CFL performed better than the others according to all three classes of metrics. In summary over all structures, the ranking by the Dice coefficient was CFL, BAM, joint EMS and PAM. The Hausdorff distance ranked the methods as CFL, joint PAM and BAM, EMS, whilst percentage absolute volumetric difference ranked them as joint CFL and PAM, joint BAM and EMS. Furthermore, as we had four methods of performing segmentation, we investigated whether the results obtained by each method were more similar to each other than to the manual segmentations using Williams' Index. Reassuringly, the Williams' Index was close to 1 for most subjects (mean = 1.02, sd = 0.05), indicating better agreement of each method with the gold standard than with the other methods. However, 2% of cases (mainly amygdala and nucleus accumbens) had values outside 3 standard deviations of the mean. © 2009 Elsevier Inc. All rights reserved.
Document Type: Article
Source: Scopus
Schobel, S.A.a b , Kelly, M.A.a , Corcoran, C.M.a b , Van Heertum, K.a b , Seckinger, R.a c , Goetz, R.b c , Harkavy-Friedman, J.b , Malaspina, D.b c
Anterior hippocampal and orbitofrontal cortical structural brain abnormalities in association with cognitive deficits in schizophrenia
(2009) Schizophrenia Research, 114 (1-3), pp. 110-118.
a Center for Prevention and Evaluation (COPE), New York State Psychiatric Institute, United States
b Department of Psychiatry, Columbia University, College of Physicians and Surgeons, United States
c Department of Psychiatry, New York University, New York, NY, United States
Abstract
Objective: Numerous studies have implicated the hippocampus and prefrontal cortex in schizophrenia. However, precisely which subregions of the hippocampus and prefrontal cortex are abnormal remain unknown. Our study goal was to investigate the structure of the anterior hippocampus, posterior hippocampus, dorsolateral prefrontal cortex (DLPFC), and orbitofrontal cortex (OFC) simultaneously in thirty-eight patients with schizophrenia and twenty-nine controls to determine which of these subregions are abnormal in schizophrenia. As an exploratory study goal, we investigated the relation of neurocognition to brain structure in schizophrenia patients. Method: We generated detailed structural magnetic resonance imaging data and compared hippocampal and prefrontal subregional structural brain volumes between schizophrenia and control groups. We obtained a neurocognitive test battery in schizophrenia patients and studied the association of abnormal brain structures to neurocognition. Results: Structural brain abnormalities were pinpointed to the left anterior hippocampus and left OFC in schizophrenia patients, which were both significantly reduced in volume. The DLPFC and posterior hippocampus, though numerically decreased in volume, were not significantly decreased. Anterior hippocampal volumes were more strongly associated with OFC volumes in schizophrenia patients compared to controls. By contrast, DLPFC volume was unrelated to anterior or posterior hippocampal volume. Both the anterior hippocampus and OFC were independently related to cognitive abnormalities common in schizophrenia, including indices of verbal, language, and executive functions. The DLPFC and posterior hippocampal volumes were unrelated to cognitive measures. Conclusions: These findings highlight related abnormalities of the anterior hippocampus and OFC in schizophrenia, which may shed light on the pathophysiology of the disorder.
Author Keywords
Hippocampus; Magnetic resonance imaging; Neuropsychology; Prefrontal cortex; Schizophrenia
Document Type: Article
Source: Scopus
Morra, J.H.a , Tu, Z.a , Apostolova, L.G.a b , Green, A.E.a b , Avedissian, C.a , Madsen, S.K.a , Parikshak, N.a , Hua, X.a , Toga, A.W.a , Jack Jr., C.R.c , Schuff, N.d , Weiner, M.W.d e , Thompson, P.M.a
Automated 3D mapping of hippocampal atrophy and its clinical correlates in 400 subjects with Alzheimer's disease, mild cognitive impairment, and elderly controls
(2009) Human Brain Mapping, 30 (9), pp. 2766-2788. Cited 1 time.
a Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, 635 Charles Young Drive, Los Angeles, CA 90095-1769, United States
b Department of Neurology, UCLA School of Medicine, Los Angeles, CA, United States
c Mayo Clinic College of Medicine, Rochester, MN, United States
d Department of Veterans Affairs Medical Center, Department of Radiology, UC San Francisco, San Francisco, CA, United States
e Department of Medicine and Psychiatry, UC San Francisco, San Francisco, CA, United States
Abstract
We used a new method we developed for automated hippocampal segmentation, called the auto context model, to analyze brain MRI scans of 400 subjects from the Alzheimer's disease neuroimaging initiative. After training the classifier on 21 hand-labeled expert segmentations, we created binary maps of the hippocampus for three age- and sex-matched groups: 100 subjects with Alzheimer's disease (AD), 200 with mild cognitive impairment (MCI) and 100 elderly controls (mean age: 75.84; SD: 6.64). Hippocampal traces were converted to parametric surface meshes and a radial atrophy mapping technique was used to compute average surface models and local statistics of atrophy. Surface-based statistical maps visualized links between regional atrophy and diagnosis (MCI versus controls: P = 0.008; MCI versus AD: P = 0.001), mini-mental state exam (MMSE) scores, and global and sum-ofboxes clinical dementia rating scores (CDR; all P < 0.0001, corrected). Right but not left hippocampal atrophy was associated with geriatric depression scores (P = 0.004, corrected); hippocampal atrophy was not associated with subsequent decline in MMSE and CDR scores, educational level, ApoE genotype, systolic or diastolic blood pressure measures, or homocysteine. We gradually reduced sample sizes and used false discovery rate curves to examine the method's power to detect associations with diagnosis and cognition in smaller samples. Forty subjects were sufficient to discriminate AD from normal and correlate atrophy with CDR scores; 104, 200, and 304 subjects, respectively, were required to correlate MMSE with atrophy, to distinguish MCI from normal, and MCI from AD. © 2009 Wiley-Liss, Inc.
Author Keywords
ADNI; Automated segmentation; Hippocampus
Document Type: Article
Source: Scopus
Lin, X.-B.a b , Qiu, T.-S.a , Ruan, S.b , Morain-Nicolier, F.b
Research on intensity and shape based non-rigid image registration
(2009) Chinese Journal of Biomedical Engineering, 28 (4), pp. 615-619.
a School of Electronic and Information Engineering, Dalian University of Technology, Dalian 116023, China
b CReSTIC, IUT de Troyes, 10026 Troyes Cedex, France
Author Keywords
Brain; MRI; Non-rigid registration; Segmentation; Shape
Document Type: Article
Source: Scopus
Grauer, D.a , Cevidanes, L.S.H.b , Proffit, W.R.c
Working with DICOM craniofacial images
(2009) American Journal of Orthodontics and Dentofacial Orthopedics, 136 (3), pp. 460-470.
a Department of Orthodontics, School of Dentistry, University of North Carolina, Chapel Hill, NC, United States
b Department of Orthodontics, School of Dentistry, University of North Carolina, Chapel Hill, NC, United States
c Department of Orthodontics, School of Dentistry, University of North Carolina, Chapel Hill, NC, United States
Abstract
The increasing use of cone-beam computed tomography (CBCT) requires changes in our diagnosis and treatment planning methods as well as additional training. The standard for digital computed tomography images is called digital imaging and communications in medicine (DICOM). In this article we discuss the following concepts: visualization of CBCT images in orthodontics, measurement in CBCT images, creation of 2-dimensional radiographs from DICOM files, segmentation engines and multimodal images, registration and superimposition of 3-dimensional (3D) images, special applications for quantitative analysis, and 3D surgical prediction. CBCT manufacturers and software companies are continually working to improve their products to help clinicians diagnose and plan treatment using 3D craniofacial images. © 2009 American Association of Orthodontists.
Document Type: Article
Source: Scopus
Mechanic-Hamilton, D.a b , Korczykowski, M.a , Yushkevich, P.A.c , Lawler, K.d , Pluta, J.a , Glynn, S.a d , Tracy, J.I.e , Wolf, R.L.c , Sperling, M.R.e , French, J.A.d , Detre, J.A.a c d
Hippocampal volumetry and functional MRI of memory in temporal lobe epilepsy
(2009) Epilepsy and Behavior, 16 (1), pp. 128-138.
a Center for Functional Neuroimaging, University of Pennsylvania, Philadelphia, PA, United States
b Department of Psychology, Drexel University, Philadelphia, PA, United States
c Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States
d Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
e Department of Neurology, Thomas Jefferson University, Philadelphia, PA, United States
Abstract
This study examined the utility of structural and functional MRI at 1.5 and 3 T in the presurgical evaluation and prediction of postsurgical cognitive outcome in temporal lobe epilepsy (TLE). Forty-nine patients undergoing presurgical evaluation for temporal lobe (TL) resection and 25 control subjects were studied. Patients completed standard presurgical evaluations, including the intracarotid amobarbital test (IAT) and neuropsychological testing. During functional imaging, subjects performed a complex visual scene-encoding task. High-resolution structural MRI scans were used to quantify hippocampal volumes. Both structural and functional imaging successfully lateralized the seizure focus and correlated with IAT memory lateralization, with improvement for functional imaging at 3 T as compared with 1.5 T. Ipsilateral structural and functional MRI data were related to cognitive outcome, and greater functional asymmetry was related to earlier age at onset. These findings support continued investigation of the utility of MRI and fMRI in the presurgical evaluation of TLE. © 2009 Elsevier Inc. All rights reserved.
Author Keywords
Epilepsy surgery; Functional magnetic resonance imaging; Hippocampal volume; Intracarotid amobarbital test; Neuropsychological outcome; Temporal lobe epilepsy; Wada
Document Type: Article
Source: Scopus
Calvini, P.a , Chincarini, A.b , Gemme, G.b , Penco, M.A.a , Squarcia, S.a , Nobili, F.a , Rodriguez, G.a , Bellotti, R.c , Catanzariti, E.d , Cerello, P.e , De Mitri, I.f , Fantacci, M.E.g
Automatic analysis of medial temporal lobe atrophy from structural MRIs for the early assessment of Alzheimer disease
(2009) Medical Physics, 36 (8), pp. 3737-3747.
a Dipartimento di Fisica, Università di Genova, I-16146 Genova, Italy
b Istituto Nazionale di Fisica Nucleare, Sezione di Genova, I-16146 Genova, Italy
c Neurofisiologia Clinica, Dipartimento di Neuroscienze, Oftalmologia e Genetica, Azienda Ospedale-Universit S. Martino, I-16132 Genova, Italy
d Dipartimento Interateneo di Fisica M. Merlin and TIRES, Universita Degli Studi di Bari, I-70126 Bari, Italy
e Dipartimento di Scienze Fisiche, Istituto Nazionale di Fisica Nucleare, Universit di Napoli, I-80126 Napoli, Italy
f Istituto Nazionale di Fisica Nucleare, Sezione di Torino, I-10125, Torino, Italy
g Dipartimento di Fisica, Istituto Nazionale di Fisica Nucleare, Universit Del Salento, I-73100 Lecce, Italy
Abstract
The purpose of this study is to develop a software for the extraction of the hippocampus and surrounding medial temporal lobe (MTL) regions from T1-weighted magnetic resonance (MR) images with no interactive input from the user, to introduce a novel statistical indicator, computed on the intensities in the automatically extracted MTL regions, which measures atrophy, and to evaluate the accuracy of the newly developed intensity-based measure of MTL atrophy to (a) distinguish between patients with Alzheimer disease (AD), patients with amnestic mild cognitive impairment (aMCI), and elderly controls by using established criteria for patients with AD and aMCI as the reference standard and (b) infer about the clinical outcome of aMCI patients. For the development of the software, the study included 61 patients with mild AD (17 men, 44 women; mean age±standard deviation (SD), 75.8years±7.8; Mini Mental State Examination (MMSE) score, 24.1±3.1), 42 patients with aMCI (11 men, 31 women; mean age±SD, 75.2years±4.9; MMSE score, 27.9±1.9), and 30 elderly healthy controls (10 men, 20 women; mean age±SD, 74.7years±5.2; MMSE score, 29.1±0.8). For the evaluation of the statistical indicator, 150 patients with mild AD (62 men, 88 women; mean age±SD, 76.3years±5.8; MMSE score, 23.2±4.1), 247 patients with aMCI (143 men, 104 women; mean age±SD, 75.3years±6.7; MMSE score, 27.0±1.8), and 135 elderly healthy controls (61 men, 74 women; mean age±SD, 76.4years±6.1). Fifty aMCI patients were evaluated every 6 months over a 3 year period to assess conversion to AD. For each participant, two subimages of the MTL regions were automatically extracted from T1-weighted MR images with high spatial resolution. An intensity-based MTL atrophy measure was found to separate control, MCI, and AD cohorts. Group differences wereassessed by using two-sample t test. Individual classification was analyzed by using receiver operating characteristic (ROC) curves. Compared to controls, significant differences in the intensity-based MTL atrophy measure were detected in both groups of patients (AD vs controls, 0.28±0.03 vs 0.34±0.03, P<0.001; aMCI vs controls, 0.31±0.03 vs 0.34±0.03, P<0.001). Moreover, the subgroup of aMCI converters was significantly different from controls (0.27±0.034 vs 0.34±0.03, P<0.001). Regarding the ROC curve for intergroup discrimination, the area under the curve was 0.863 for AD patients vs controls, 0.746 for all aMCI patients vs controls, and 0.880 for aMCI converters vs controls. With specificity set at 85%, the sensitivity was 74% for AD vs controls, 45% for aMCI vs controls, and 83% for aMCI converters vs controls. The automated analysis of MTL atrophy in the segmented volume is applied to the early assessment of AD, leading to the discrimination of aMCI converters with an average 3 year follow-up. This procedure can provide additional useful information in the early diagnosis of AD. © 2009 American Association of Physicists in Medicine.
Author Keywords
Alzheimer disease; Hippocampus; Image analysis; Magnetic resonance imaging
Document Type: Article
Source: Scopus
Heimann, T.a , Van Ginneken, B.b , Styner, M.A.c , Arzhaeva, Y.b , Aurich, V.d , Bauer, C.e , Beck, A.a , Becker, C.d h , Beichel, R.f , Bekes, G.k , Bello, F.l , Binnig, G.n , Bischof, H.e , Bornik, A.e , Cashman, P.M.M.m , Chi, Y.m , Córdova, A.i , Dawant, B.M.o , Fidrich, M.k , Furst, J.D.q , Furukawa, D.r , Grenacher, L.j , Hornegger, J.s , Kainmüller, D.u , Kitney, R.I.m , Kobatake, H.r , Lamecker, H.u , Lange, T.v , Lee, J.w , Lennon, B.p , Li, R.o , Li, S.p , Meinzer, H.-P.a , Németh, G.k , Raicu, D.S.q , Rau, A.-M.a , Van Rikxoort, E.M.b , Rousson, M.x , Ruskó, L.k , Saddi, K.A.x , Schmidt, G.n , Seghers, D.y , Shimizu, A.r , Slagmolen, P.y , Sorantin, E.g , Soza, G.t , Susomboon, R.q , Waite, J.M.p , Wimmer, A.s , Wolf, I.a
Comparison and evaluation of methods for liver segmentation from CT datasets
(2009) IEEE Transactions on Medical Imaging, 28 (8), art. no. 4781564, pp. 1251-1265.
a Division of Medical and Biological Informatics, German Cancer Research Center, 69121 Heidelberg, Germany
b Image Sciences Institute, University Medical Center Utrecht, 3584 CX Utrecht, Netherlands
c Department of Psychiatry and Computer Science, University of North Carolina, Chapel Hill, NC 27514, United States
d Institute for Computer Science, Heinrich-Heine University Düsseldorf, 40225 Düsseldorf, Germany
e Institute for Computer Graphics and Vision, Graz University of Technology, 8010 Graz, Austria
f Department of Electrical and Computer Engineering, Department of Internal Medicine, University of Iowa, Iowa City, IA 52242, United States
g Department of Radiology, Medical University Graz, A-8036 Graz, Austria
h Department of Clinical Radiology, University Hospital of Munich, 81377 Munich, Germany
i Department of Oncology, Clínica Alemana de Santiago, Santiago, Chile
j Department of Diagnostic Radiology, University Hospital of Heidelberg, 69118 Heidelberg, Germany
k GE Hungary ZRT, Healthcare Division, 6720 Szeged, Hungary
l Department of Biosurgery and Surgical Technology, Imperial College London, SW7 2AZ London, United Kingdom
m Department of Bioengineering, Imperial College London, SW7 2AZ London, United Kingdom
n Definiens AG Research, 80339 Munich, Germany
o Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN 37235, United States
p Pathfinder Therapeutics, Inc., Nashville, TN 37203, United States
q Intelligent Multimedia Processing Laboratory, School of Computing, College of Computing and Digital Media, Chicago, IL 60604, United States
r Tokyo University of, Agriculture and Technology, Japan
s Department of Pattern Recognition, Department of Computer Science, Friedrich-Alexander University Erlangen-Nuremberg, 91058 Erlangen, Germany
t Computed Tomography, Healthcare Sector, Siemens AG, Forchheim, Germany
u Zuse Institute Berlin, 14195 Berlin, Germany
v Department of Surgery and Surgical Oncology, Chariteacute;-Universitätsmedizin, 10117 Berlin, Germany
w Department of Digital Media, Catholic University of Korea, South Korea
x Department of Imaging and Visualization, Siemens Corporate Research, Princeton, NJ 08540, United States
y Medical Image Computing (ESAT/PSI), Faculties of Medicine and Engineering, University Hospital Gasthuisberg, 3000 Leuven, Belgium
Abstract
This paper presents a comparison study between 10 automatic and six interactive methods for liver segmentation from contrast-enhanced CT images. It is based on results from the "MICCAI 2007 Grand Challenge" workshop, where 16 teams evaluated their algorithms on a common database. A collection of 20 clinical images with reference segmentations was provided to train and tune algorithms in advance. Participants were also allowed to use additional proprietary training data for that purpose. All teams then had to apply their methods to 10 test datasets and submit the obtained results. Employed algorithms include statistical shape models, atlas registration, level-sets, graph-cuts and rule-based systems. All results were compared to reference segmentations five error measures that highlight different aspects of segmentation accuracy. All measures were combined according to a specific scoring system relating the obtained values to human expert variability. In general, interactive methods reached higher average scores than automatic approaches and featured a better consistency of segmentation quality. However, the best automatic methods (mainly based on statistical shape models with some additional free deformation) could compete well on the majority of test images. The study provides an insight in performance of different segmentation approaches under real-world conditions and highlights achievements and limitations of current image analysis techniques. © 2009 IEEE.
Author Keywords
Evaluation; Liver; Segmentation
Document Type: Article
Source: Scopus
Scherrer, B.a b , Forbes, F.c d , Garbay, C.c e , Dojat, M.a e
Distributed local MRF models for tissue and structure brain segmentation
(2009) IEEE Transactions on Medical Imaging, 28 (8), art. no. 4785215, pp. 1278-1295.
a INSERM, 38043 Grenoble, France
b CNRS, Laboratoire LIG-Institut IMAG, MAGMA, 38041 Grenoble, France
c INRIA, Laboratoire Jean Kuntzmann, MISTIS Team, 38330 Montbonnot-Saint-Martin, France
d Université Joseph Fourier, 38400 Grenoble, France
e Universite Joseph Fourier, 38400 Grenoble, France
Abstract
Accurate tissue and structure segmentation of magnetic resonance (MR) brain scans is critical in several applications. In most approaches this task is handled through two sequential steps. We propose to carry out cooperatively both tissue and sub-cortical structure segmentation by distributing a set of local and cooperative Markov random field (MRF) models Tissue segmentation is performed by partitioning the volume into subvolumes where local MRFs are estimated in cooperation with their neighbors to ensure consistency. Local estimation fits precisely to the local intensity distribution and thus handles nonuniformity of intensity without any bias field modelization. Similarly, subcortical structure segmentation is performed via local MRF models that integrate localization constraints provided by a priori fuzzy description of brain anatomy. Subcortical structure segmentation is not reduced to a subsequent processing step but joined with tissue segmentation: the two procedures cooperate to gradually and conjointly improve model accuracy. We propose a framework to implement this distributed modeling integrating cooperation, coordination, and local model checking in an efficient way. Its evaluation was performed using both phantoms and real 3 T brain scans, showing good results and in particular robustness to nonuniformity and noise with a low computational cost. This original combination of local MRF models, including anatomical knowledge, appears as a powerful and promising approach for MR brain scan segmentation. © 2009 IEEE.
Author Keywords
Em estimation; Human brain; Magnetic resonance imaging (MRI); Markov random field (MRF)
Document Type: Article
Source: Scopus
Levinski, K., Sourin, A., Zagorodnov, V.
3D visualization and segmentation of brain MRI data
(2009) GRAPP 2009 - Proceedings of the 4th International Conference on Computer Graphics Theory and Applications, pp. 111-118.
Nanyang Technological University, NanyangAvenue, Singapore, Singapore
Abstract
Automatic segmentation of brain MRI data usually leaves some segmentation errors behind that are to be subsequently removed interactively using computer graphics tools. This interactive removal is normally performed by operating on individual 2D slices. It is very tedious and stili leaves some segmentation errors which are not visible on the slices. We have proposed to perform a novel 3D interactive correction of brain segmentation errors introduced by the fully automatic segmentation algorithms. We have developed the tool which is based on a 3D semi-automatic propagation algorithm. The paper describes the implementation principles of the proposed tool and illustrates its application.
Author Keywords
3D visualization; Brain; MRI data; Segmentation
Document Type: Conference Paper
Source: Scopus
Zhang, Y.a , Wang, W.a , Liang, X.a , Bazilevs, Y.b , Hsu, M.-C.b , Kvamsdal, T.c , Brekken, R.d , Isaksen, J.e
High-fidelity tetrahedral mesh generation from medical imaging data for fluid-structure interaction analysis of cerebral aneurysms
(2009) CMES - Computer Modeling in Engineering and Sciences, 42 (2), pp. 131-148. Cited 1 time.
a Department of Mechanical Engineering, Carnegie Mellon University, United States
b Department of Structural Engineering, University of California, San Diego, United States
c Department of Applied Mathematics, SINTEF Information and Communication Technology, Trondheim, Norway
d Department of Medical Technology, SINTEF Health Research, Trondheim, Norway
e Department of Neurosurgery, University Hospital of North Norway, TromsØ, Norway
Abstract
This paper describes a comprehensive and high-fidelity finite element meshing approach for patient-specific arterial geometries from medical imaging data, with emphasis on cerebral aneurysm configurations. The meshes contain both the blood volume and solid arterial wall, and are compatible at the fluid-solid interface. There are four main stages for this meshing method: 1) Image segmentation and geometric model construction; 2) Tetrahedral mesh generation for the fluid volume using the octree-based method; 3) Mesh quality improvement stage, in which edge-contraction, pillowing, optimization, geometric flow smoothing, and mesh cutting are applied to the fluid mesh; and 4) Mesh generation for the blood vessel wall based on the boundary layer generation technique. The constructed meshes are extensively employed in a fully-coupled fluid-structure interaction analysis of vascular blood flow. This paper presents several case studies of hemodynamics in patient-specific cerebral aneurysms. copy; 2009 Tech Science Press.
Author Keywords
Cerebral aneurysm; Fluid-structure interaction; Tetrahedral meshing
Document Type: Article
Source: Scopus
Cevidanes, L.H.C.a , Heymann, G.b , Cornelis, M.A.c , DeClerck, H.J.d , Tulloch, J.F.C.e
Superimposition of 3-dimensional cone-beam computed tomography models of growing patients
(2009) American Journal of Orthodontics and Dentofacial Orthopedics, 136 (1), pp. 94-99.
a Department of Orthodontics, School of Dentistry, University of North Carolina, Chapel Hill, NC, United States
c Experimental Morphology Unit, Department of Orthdontics, Université Catholique de Louvain, Brussels, Belgium
e Department of Orthodontics, School of Dentistry, University of North Carolina, Chapel Hill, NC, United States
Abstract
Introduction: The objective of this study was to evaluate a new method for superimposition of 3-dimensional (3D) models of growing subjects. Methods: Cone-beam computed tomography scans were taken before and after Class III malocclusion orthopedic treatment with miniplates. Three observers independently constructed 18 3D virtual surface models from cone-beam computed tomography scans of 3 patients. Separate 3D models were constructed for soft-tissue, cranial base, maxillary, and mandibular surfaces. The anterior cranial fossa was used to register the 3D models of before and after treatment (about 1 year of follow-up). Results: Three-dimensional overlays of superimposed models and 3D color-coded displacement maps allowed visual and quantitative assessment of growth and treatment changes. The range of interobserver errors for each anatomic region was 0.4 mm for the zygomatic process of maxilla, chin, condyles, posterior border of the rami, and lower border of the mandible, and 0.5 mm for the anterior maxilla soft-tissue upper lip. Conclusions: Our results suggest that this method is a valid and reproducible assessment of treatment outcomes for growing subjects. This technique can be used to identify maxillary and mandibular positional changes and bone remodeling relative to the anterior cranial fossa. © 2009 American Association of Orthodontists.
Document Type: Article
Source: Scopus
Huang, A.a , Abugharbieh, R.a , Tam, R.b
A hybrid geometricstatistical deformable model for automated 3-d segmentation in brain MRI
(2009) IEEE Transactions on Biomedical Engineering, 56 (7), art. no. 4806067, pp. 1838-1848.
a Department of Electrical and Computer Engineering, University of British Columbia (UBC), Vancouver, BC V6T 1Z4, Canada
b Department of Radiology, University of British Columbia (UBC), Vancouver, BC V6T 1Z4, Canada
Abstract
We present a novel 3-D deformable model-based approach for accurate, robust, and automated tissue segmentation of brain MRI data of single as well as multiple magnetic resonance sequences. The main contribution of this study is that we employ an edge-based geodesic active contour for the segmentation task by integrating both image edge geometry and voxel statistical homogeneity into a novel hybrid geometricstatistical feature to regularize contour convergence and extract complex anatomical structures. We validate the accuracy of the segmentation results on simulated brain MRI scans of both single T1-weighted and multiple T1/T2/PD-weighted sequences. We also demonstrate the robustness of the proposed method when applied to clinical brain MRI scans. When compared to a current state-of-the-art region-based level-set segmentation formulation, our white matter and gray matter segmentation resulted in significantly higher accuracy levels with a mean improvement in Dice similarity indexes of 8.55% ( $p 0.0001$) and 10.18% ($p 0.0001$), respectively. © 2006 IEEE.
Author Keywords
3-D image segmentation; Brain segmentation; Deformable models; Geodesic active contour
Document Type: Article
Source: Scopus
Hořínek, D.a , Brezová, V.c , Nimsky, C.b , Belšan, T.e , Martinkovič, L.c , Masopust, V.a , Vrána, J.c e , Kozler, P.a , Plas, J.a , Krýsl, D.d , Varjassyová, A.d f , Ghaly, Y.c , Beneš, V.a
The MRI volumetry of the posterior fossa and its substructures in trigeminal neuralgia: A validated study
(2009) Acta Neurochirurgica, 151 (6), pp. 669-675.
a Department of Neurosurgery, Central Military Hospital Prague, Charles University, U Vojenske nemocnice 1200, Praha 6 160 00, Czech Republic
b Department of Neurosurgery, Medical Faculty, Philipps University, Baldingerstrasse, Marburg 35033, Germany
c Institute of Pathological Physiology, Second Faculty of Medicine, Charles University, Plzenska 130, Praha 5 158 00, Czech Republic
d Department of Neurology, Charles University, University Hospital Motol, V Uvalu 84, Praha 5 158 00, Czech Republic
e Department of Radiology, Central Military Hospital Prague, U Vojenske nemocnice 1200, Praha 6 160 00, Czech Republic
f Institute of Anatomy, First Faculty of Medicine, Charles University, U nemocnice 2, Praha 1 110 00, Czech Republic
Abstract
Purpose: Our aim was to determine whether the anatomical configuration of the posterior fossa and its substructures might represent a predisposition factor for the occurrence of clinical neurovascular conflict in trigeminal neuralgia (TN). Methods: We used MRI volumetry in 18 patients with TN and 15 controls. The volume of the pontomesencephalic cistern, Meckel's cave and the trigeminal nerve on the clinical and non-affected sides was compared. The reliability has been assessed in all measurements. Results: The posterior fossa volume was not different in the clinical and control groups; there was no difference between the affected and non-affected sides when measuring the pontomesencephalic cistern and Meckel's cave volume either. The volume of the clinically affected trigeminal nerve was significantly reduced, but with a higher error of measurement. Conclusions: We did not find any association between the clinical neurovascular conflict (NVC) and the size of the posterior fossa and its substructures. MRI volumetry may show the atrophy of the affected trigeminal nerve in clinical NVC. © 2009 Springer-Verlag.
Author Keywords
MRI volumetry; Neurovascular conflict; Posterior fossa; Trigeminal neuralgia; Validation
Document Type: Article
Source: Scopus
Zheng, F.a , Hui, G.b
Practical contour segmentation algorithm for small animal digital radiography image
(2009) Proceedings of SPIE - The International Society for Optical Engineering, 7280, art. no. 72800K, .
a Institute for Pattern Recognition and Artificial Intelligence, Huazhong University of Science and Technology, Wuhan, Hubei, China
b Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, Hubei, China
Abstract
In this paper a practical, automated contour segmentation technique for digital radiography image is described. Digital radiography is an imaging mode based on the penetrability of x-ray. Unlike reflection imaging mode such as visible light camera, the pixel brightness represents the summation of the attenuations on the photon thoroughfare. It is not chromophotograph but gray scale picture. Contour extraction is of great importance in medical applications, especially in non-destructive inspection. Manual segmentation techniques include pixel selection, geometrical boundary selection and tracing. But it relies heavily on the experience of the operators, and is time-consuming. Some researchers try to find contours from the intensity jumping characters around them. However these characters also exist in the juncture of bone and soft tissue. The practical way is back to the primordial threshold algorithm. This research emphasizes on how to find the optimal threshold. A high resolution digital radiography system is used to provide the oriental gray scale image. A mouse is applied as the sample of this paper to show the feasibility of the algorithm. © 2009 SPIE.
Author Keywords
Automatic; Contour extraction; Digital radiography; Small animal; Threshold segmentation
Document Type: Conference Paper
Source: Scopus
Pluta, J.a b c , Avants, B.B.a b , Glynn, S.a b , Awate, S.a b , Gee, J.C.a b , Detre, J.A.a b
Appearance and incomplete label matching for diffeomorphic template based hippocampus segmentation
(2009) Hippocampus, 19 (6), pp. 565-571.
a Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States
b Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
c Departments of Radiology and Neurology, University of Pennsylvania, Philadelphia, PA 19104, United States
Abstract
We present a robust, high-throughput, semiautomated template-based protocol for segmenting the hippocampus in temporal lobe epilepsy. The semiautomated component of this approach, which minimizes user effort while maximizing the benefit of human input to the algorithm, relies on "incomplete labeling." Incomplete labeling requires the user to quickly and approximately segment a few key regions of the hippocampus through a user-interface. Subsequently, this partial labeling of the hippocampus is combined with image similarity terms to guide volumetric diffeomorphic normalization between an individual brain and an unbiased disease-specific template, with fully labeled hippocampi. We solve this many-to-few and few-to-many matching problem, and gain robustness to inter and intrarater variability and small errors in user labeling, by embedding the template-based normalization within a probabilistic framework that examines both label geometry and appearance data at each label. We evaluate the reliability of this framework with respect to manual labeling and show that it increases minimum performance levels relative to fully automated approaches and provides high inter-rater reliability. Thus, this approach does not require expert neuroanatomical training and is viable for high-throughput studies of both the normal and the highly atrophic hippocampus. © 2009 Wiley-Liss, Inc.
Author Keywords
Hippocampus; Normalization; Segmentation
Document Type: Article
Source: Scopus
Mannion, D.J.a b , McDonald, J.S.a , Clifford, C.W.G.a b
Discrimination of the local orientation structure of spiral Glass patterns early in human visual cortex
(2009) NeuroImage, 46 (2), pp. 511-515.
a Colour, Form, and Motion Lab, School of Psychology, The University of Sydney, Australia
b Australian Research Council Centre of Excellence in Vision Science
Abstract
The local orientation structure of a visual image is fundamental to the perception of spatial form. Reports of reliable orientation-selective modulations in the pattern of fMRI activity have demonstrated the potential for investigating the representation of orientation in the human visual cortex. Orientation-selective voxel responses could arise from anisotropies in the preferred orientations of pooled neurons due to the random sampling of the cortical surface. However, it is unclear whether orientation-selective voxel responses reflect biases in the underlying distribution of neuronal orientation preference, such as the demonstrated over-representation of radial orientations (those collinear with fixation). Here, we investigated whether stimuli balanced in their radial components could evoke orientation-selective biases in voxel activity. We attempted to discriminate the sense of spiral Glass patterns (opening anti-clockwise or clockwise), in which the local orientation structure was defined by the placement of paired dots at an orientation offset from the radial. We found that information within the spatial pattern of fMRI responses in each of V1, V2, V3, and V3A/B allowed discrimination of the spiral sense with accuracies significantly above chance. This result demonstrates that orientation-selective voxel responses can arise without the influence of a radial bias. Furthermore, the finding indicates the importance of the early visual areas in representing the local orientation structure for the perception of complex spatial form. © 2009 Elsevier Inc. All rights reserved.
Author Keywords
Computational neuroimaging; fMRI; Multivariate analysis; Orientation; Spatial vision; V1
Document Type: Article
Source: Scopus
Shen, L.a b c , Firpi, H.A.a , Saykin, A.J.a , West, J.D.a
Parametric surface modeling and registration for comparison of manual and automated segmentation of the hippocampus
(2009) Hippocampus, 19 (6), pp. 588-595.
a Department of Radiology, IU Center for Neuroimaging, Indiana University School of Medicine, Indianapolis, IN, United States
b Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, United States
c Department of Radiology, Center for Neuroimaging, Indiana University School of Medicine, Indianapolis, IN 46202, United States
Abstract
Accurate and efficient segmentation of the hippocampus from brain images is a challenging issue. Although experienced anatomic tracers can be reliable, manual segmentation is a time consuming process and may not be feasible for large-scale neuroimaging studies. In this article, we compare an automated method, FreeSurfer (V4), with a published manual protocol on the determination of hippocampal boundaries from magnetic resonance imaging scans, using data from an existing mild cognitive impairment/Alzheimer's disease cohort. To perform the comparison, we develop an enhanced spherical harmonic processing framework to model and register these hippocampal traces. The framework treats the two hippocampi as a single geometric configuration and extracts the positional, orientation, and shape variables in a multiobject setting. We apply this framework to register manual tracing and Free-Surfer results together and the two methods show stronger agreement on position and orientation than shape measures. Work is in progress to examine a refined FreeSurfer segmentation strategy and an improved agreement on shape features is expected. © 2009 Wiley-Liss, Inc.
Author Keywords
Hippocampus; Registration; Segmentation; Shape analysis
Document Type: Article
Source: Scopus
Parnell, S.E.a d , O'Leary-Moore, S.K.a , Godin, E.A.a , Dehart, D.B.a , Johnson, B.W.c , Allan Johnson, G.c , Styner, M.A.b , Sulik, K.K.a
Magnetic resonance microscopy defines ethanol-induced brain abnormalities in prenatal mice: Effects of acute insult on gestational day 8
(2009) Alcoholism: Clinical and Experimental Research, 33 (6), pp. 1001-1011.
a Bowles Center for Alcohol Studies, University of North Carolina, Chapel Hill, NC
b Neurodevelopmental Disorders Research Center, University of North Carolina, Chapel Hill, NC
c Center for in Vivo Microscopy, Duke University, Durham, NC
d Bowles Center for Alcohol Studies, University of North Carolina, Chapel Hill, NC 27599-7178
Abstract
Background: Magnetic resonance microscopy (MRM), magnetic resonance imaging (MRI) at microscopic levels, provides unprecedented opportunities to aid in defining the full spectrum of ethanol's insult to the developing brain. This is the first in a series of reports that, collectively, will provide an MRM-based atlas of developmental stage-dependent structural brain abnormalities in a Fetal Alcohol Spectrum Disorders (FASD) mouse model. The ethanol exposure time and developmental stage examined for this report is gestational day (GD) 8 in mice, when the embryos are at early neurulation stages; stages present in humans early in the fourth week postfertilization. Methods: For this study, pregnant C57Bl/6J mice were administered an ethanol dosage of 2.8 g/kg intraperitoneally at 8 days, 0 hour and again at 8 days, 4 hours postfertilization. On GD 17, fetuses that were selected for MRM analyses were immersion fixed in a Bouin's/Prohance® solution. Control fetuses from vehicle-treated dams were stage-matched to those that were ethanol-exposed. The fetal mice were scanned ex vivo at 7.0 T and 512 × 512 × 1024 image arrays were acquired using 3-D spin warp encoding. The resulting 29 μm (isotropic) resolution images were processed using ITK-SNAP, a 3-D segmentation/ visualization tool. Linear and volume measurements were determined for selected brain, head, and body regions of each specimen. Comparisons were made between control and treated fetuses, with an emphasis on determining (dis)proportionate changes in specific brain regions. Results: As compared with controls, the crown-rump lengths of stage-matched ethanol-exposed GD 17 fetuses were significantly reduced, as were brain and whole body volumes. Volume reductions were notable in every brain region examined, with the exception of the pituitary and septal region, and were accompanied by increased ventricular volumes. Disproportionate regional brain volume reductions were most marked on the right side and were significant for the olfactory bulb, hippocampus, and cerebellum; the latter being the most severely affected. Additionally, the septal region and the pituitary were disproportionately large. Linear measures were consistent with those of volume. Other dysmorphologic features noted in the MR scans were choanal stenosis and optic nerve coloboma. Conclusions: This study demonstrates that exposure to ethanol occurring in mice at stages corresponding to the human fourth week postfertilization results in structural brain abnormalities that are readily identifiable at fetal stages of development. In addition to illustrating the utility of MR microscopy for analysis of an FASD mouse model, this work provides new information that confirms and extends human clinical observations. It also provides a framework for comparison of structural brain abnormalities resulting from ethanol exposure at other developmental stages and dosages. © 2009 by the Research Society on Alcoholism.
Author Keywords
Brain; Development; Fetal alcohol spectrum disorders; Magnetic resonance microscopy; Mouse
Document Type: Article
Source: Scopus
Escolar, M.L.a g , Poe, M.D.b , Smith, J.K.c , Gilmore, J.H.d , Kurtzberg, J.f , Lin, W.c , Styner, M.d e
Diffusion tensor imaging detects abnormalities in the corticospinal tracts of neonates with infantile Krabbe disease
(2009) American Journal of Neuroradiology, 30 (5), pp. 1017-1021.
a Program for Neurodevelopmental Function in Rare Disorders, Center for the Study of Development and Learning, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
b FPG Child Development Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
c Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
d Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
e Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
f Pediatric Blood and Marrow Transplantation Program, Duke University Medical Center, Durham, NC, United States
g University of North Carolina at Chapel Hill, 1450 Raleigh Rd, Chapel Hill, NC 27517, United States
Abstract
BACKGROUND AND PURPOSE: It is not possible to determine if neonates diagnosed with Krabbe disease through statewide neonate screening programs will develop the disease as infants, juveniles, or adults. The only available treatment for this fatal neurodegenerative condition is unrelated umbilical cord transplantation, but this treatment is only effective before clinical symptoms appear. Therefore, a marker of disease progression is needed. The purpose of this study was to evaluate the use of diffusion tensor imaging (DTI) with fiber tracking in identifying early changes in major motor tracts of asymptomatic neonates with infantile Krabbe disease. MATERIALS AND METHODS: Six neonates with infantile Krabbe disease identified because of family history underwent brain MR imaging within the first 4 weeks of life. Six-direction DTI and quantitative tractography of the corticospinal tracts were performed. Hypothesis tests, 1 for each hemisphere, were used to determine whether the fractional anisotropy (FA) ratio of the neonates with infantile Krabbe disease was significantly different from that of 45 age- and sex-matched controls. RESULTS: The average FA ratio for patients with Krabbe disease was 0.89 and 0.87 for left and right tracts, respectively (P = .002 and < .001). After adjusting for gestational age, gestational age at birth, birth weight, sex, and race, the 6 patients with Krabbe disease had significantly lower FA values than the controls (P < .001). CONCLUSIONS: DTI with quantitative tractography detected significant differences in the corticospinal tracts of asymptomatic neonates who had the early-onset form of Krabbe disease. Once standardized and validated, this tool has the potential to be used as a marker of disease progression in neonates diagnosed through statewide neonate screening programs.
Document Type: Article
Source: Scopus
Abeysinghe, S.S., Ju, T.
Interactive skeletonization of intensity volumes
(2009) Visual Computer, 25 (5-7), pp. 627-635.
Washington University in St. Louis, St. Louis, IL, United States
Abstract
We present an interactive approach for identifying skeletons (i.e. centerlines) in intensity volumes, such as those produced by biomedical imaging. While skeletons are very useful for a range of image analysis tasks, it is extremely difficult to obtain skeletons with correct connectivity and shape from noisy inputs using automatic skeletonization methods. In this paper we explore how easy-to-supply user inputs, such as simple mouse clicking and scribbling, can guide the creation of satisfactory skeletons. Our contributions include formulating the task of drawing 3D centerlines given 2D user inputs as a constrained optimization problem, solving this problem on a discrete graph using a shortest-path algorithm, building a graphical interface for interactive skeletonization and testing it on a range of biomedical data. © Springer-Verlag 2009.
Author Keywords
Intensity volumes; Interactive; Skeletonization
Document Type: Article
Source: Scopus
Mosconi, M.W.a , Cody-Hazlett, H.a , Poe, M.D.a , Gerig, G.a , Gimpel-Smith, R.a , Piven, J.a b
Longitudinal study of amygdala volume and joint attention in 2- to 4-year-old children with autism
(2009) Archives of General Psychiatry, 66 (5), pp. 509-516.
a UNC Neurodevelopmental Disorders Research Center, University of North Carolina, Chapel Hill
b UNC Neurodevelopmental Disorders Research Center, University of North Carolina, CB#3367, Chapel Hill, NC 27599-3367
Abstract
Context: Cerebral cortical volume enlargement has been reported in 2- to 4-year-olds with autism. Little is known about the volume of subregions during this period of development. The amygdala is hypothesized to be abnormal in volume and related to core clinical features in autism. Objectives: To examine amygdala volume at 2 years with follow-up at 4 years of age in children with autism and to explore the relationship between amygdala volume and selected behavioral features of autism. Design: Longitudinal magnetic resonance imaging study. Setting: University medical setting. Participants: Fifty autistic and 33 control (11 devel- opmentally delayed, 22 typically developing) children between 18 and 35 months (2 years) of age followed up at 42 to 59 months (4 years) of age. Main Outcome Measures: Amygdala volumes in relation to joint attention ability measured with a new observational coding system, the Social Orienting Continuum and Response Scale; group comparisons including total tissue volume, sex, IQ, and age as covariates. Results: Amygdala enlargement was observed in subjects with autism at both 2 and 4 years of age. Significant change over time in volume was observed, although the rate of change did not differ between groups. Amygdala volume was associated with joint attention ability at age 4 years in subjects with autism. Conclusions: The amygdala is enlarged in autism relative to controls by age 2 years but shows no relative increase in magnitude between 2 and 4 years of age. A significant association between amygdala volume and joint attention suggests that alterations to this structure may be linked to a core deficit of autism. © 2009 American Medical Association. All rights reserved..
Document Type: Article
Source: Scopus
Morey, R.A.a b c e , Petty, C.M.a c , Xu, Y.a f , Pannu Hayes, J.a b c , Wagner II, H.R.b c , Lewis, D.V.a f , LaBar, K.S.a b e , Styner, M.g h , McCarthy, G.a c d
A comparison of automated segmentation and manual tracing for quantifying hippocampal and amygdala volumes
(2009) NeuroImage, 45 (3), pp. 855-866. Cited 2 times.
a Duke-UNC Brain Imaging, Analysis Center, Duke University, Durham, NC, United States
b Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, United States
c Mental Illness Research Education and Clinical Center for Post Deployment Mental Health, Durham VA Medical Center, Durham, NC, United States
d Department of Psychology, Yale University, New Haven, CT, United States
e Center for Cognitive Neuroscience, Duke University, Durham, NC, United States
f Department of Pediatrics (Neurology), Duke University, Durham, NC, United States
g Department of Computer Science, University of North Carolina, Chapel Hill, NC, United States
h Department of Psychiatry, University of North Carolina, Chapel Hill, NC, United States
Abstract
Large databases of high-resolution structural MR images are being assembled to quantitatively examine the relationships between brain anatomy, disease progression, treatment regimens, and genetic influences upon brain structure. Quantifying brain structures in such large databases cannot be practically accomplished by expert neuroanatomists using hand-tracing. Rather, this research will depend upon automated methods that reliably and accurately segment and quantify dozens of brain regions. At present, there is little guidance available to help clinical research groups in choosing such tools. Thus, our goal was to compare the performance of two popular and fully automated tools, FSL/FIRST and FreeSurfer, to expert hand tracing in the measurement of the hippocampus and amygdala. Volumes derived from each automated measurement were compared to hand tracing for percent volume overlap, percent volume difference, across-sample correlation, and 3-D group-level shape analysis. In addition, sample size estimates for conducting between-group studies were computed for a range of effect sizes. Compared to hand tracing, hippocampal measurements with FreeSurfer exhibited greater volume overlap, smaller volume difference, and higher correlation than FIRST, and sample size estimates with FreeSurfer were closer to hand tracing. Amygdala measurement with FreeSurfer was also more highly correlated to hand tracing than FIRST, but exhibited a greater volume difference than FIRST. Both techniques had comparable volume overlap and similar sample size estimates. Compared to hand tracing, a 3-D shape analysis of the hippocampus showed FreeSurfer was more accurate than FIRST, particularly in the head and tail. However, FIRST more accurately represented the amygdala shape than FreeSurfer, which inflated its anterior and posterior surfaces.
Document Type: Article
Source: Scopus
Das, S.R.a , Avants, B.B.a , Grossman, M.b , Gee, J.C.a
Registration based cortical thickness measurement
(2009) NeuroImage, 45 (3), pp. 867-879.
a Penn Image Computing and Science Laboratory (PICSL), Department of Radiology, University of Pennsylvania School of Medicine, Philadelphia, PA, United States
b Department of Neurology, University of Pennsylvania School of Medicine, Philadelphia, PA, United States
Abstract
Cortical thickness is an important biomarker for image-based studies of the brain. A diffeomorphic registration based cortical thickness (DiReCT) measure is introduced where a continuous one-to-one correspondence between the gray matter-white matter interface and the estimated gray matter-cerebrospinal fluid interface is given by a diffeomorphic mapping in the image space. Thickness is then defined in terms of a distance measure between the interfaces of this sheet like structure. This technique also provides a natural way to compute continuous estimates of thickness within buried sulci by preventing opposing gray matter banks from intersecting. In addition, the proposed method incorporates neuroanatomical constraints on thickness values as part of the mapping process. Evaluation of this method is presented on synthetic images. As an application to brain images, a longitudinal study of thickness change in frontotemporal dementia (FTD) spectrum disorder is reported. © 2008 Elsevier Inc. All rights reserved.
Author Keywords
Cortex; Deformable models; Diffeomorphism; Euclidean distance; FTD; Longitudinal; Thickness
Document Type: Article
Source: Scopus
Lewis, M.M.b c d , Smith, A.B.c , Styner, M.e f , Gu, H.f , Poole, R.c , Zhu, H.g , Li, Y.g , Barbero, X.f , Gouttard, S.f , McKeown, M.J.h , Mailman, R.B.b d f , Huang, X.a b c f
Asymmetrical lateral ventricular enlargement in Parkinson's disease
(2009) European Journal of Neurology, 16 (4), pp. 475-481.
a Department of Neurology, Pennsylvania State University, Milton S. Hershey Medical Center, 500 University Dr, H-037 Hershey, PA 17033-0850, United States
b Department of Neurology, Pennsylvania State University, Milton S. Hershey Medical Center, Hershey, PA, United States
c Department of Neurology, University of North Carolina, Chapel Hill, NC, United States
d Department of Pharmacology, Pennsylvania State University, College of Medicine, Hershey, PA
e Department of Computer Science, University of North Carolina, Chapel Hill, NC, United States
f Department of Psychiatry, University of North Carolina, Chapel Hill, NC, United States
g Department of Biostatistics, University of North Carolina, Chapel Hill, NC, United States
h Department of Medicine (Neurology), Pacific Parkinson's Research Centre, University of British Columbia, Vancouver, BC, Canada
Abstract
Background: A recent case report suggested the presence of asymmetrical lateral ventricular enlargement associated with motor asymmetry in Parkinson's disease (PD). The current study explored these associations further. Methods: Magnetic resonance imaging (3T) scans were obtained on 17 PD and 15 healthy control subjects at baseline and 12-43 months later. Baseline and longitudinal lateral ventricular volumetric changes were compared between contralateral and ipsilateral ventricles in PD subjects relative to symptom onset side and in controls relative to their dominant hand. Correlations between changes in ventricular volume and United Parkinson's disease rating scale motor scores (UPDRS-III) whilst on medication were determined. Results: The lateral ventricle contralateral to symptom onset side displayed a faster rate of enlargement compared to the ipsilateral (P = 0.004) in PD subjects, with no such asymmetry detected (P = 0.312) in controls. There was a positive correlation between ventricular enlargement and worsening motor function assessed by UPDRS-III scores (r = 0.96, P < 0.001). Discussion: There is asymmetrical lateral ventricular enlargement that is associated with PD motor asymmetry and progression. Further studies are warranted to investigate the underlying mechanism(s), as well as the potential of using volumetric measurements as a marker for PD progression. © 2009 EFNS.
Author Keywords
Lateral ventricular volume; Motor asymmetry; Parkinson's disease; Semi-automatic segmentation; Structural magnetic resonance imaging
Document Type: Article
Source: Scopus
Prastawa, M.a , Bullitt, E.b , Gerig, G.a
Simulation of brain tumors in MR images for evaluation of segmentation efficacy
(2009) Medical Image Analysis, 13 (2), pp. 297-311.
a Scientific Computing and Imaging Institute, University of Utah, 72 S. Campus Drive, WEB 3750, Salt Lake City, UT 84112, United States
b Department of Surgery, University of North Carolina, Chapel Hill, NC 27599, United States
Abstract
Obtaining validation data and comparison metrics for segmentation of magnetic resonance images (MRI) are difficult tasks due to the lack of reliable ground truth. This problem is even more evident for images presenting pathology, which can both alter tissue appearance through infiltration and cause geometric distortions. Systems for generating synthetic images with user-defined degradation by noise and intensity inhomogeneity offer the possibility for testing and comparison of segmentation methods. Such systems do not yet offer simulation of sufficiently realistic looking pathology. This paper presents a system that combines physical and statistical modeling to generate synthetic multi-modal 3D brain MRI with tumor and edema, along with the underlying anatomical ground truth, Main emphasis is placed on simulation of the major effects known for tumor MRI, such as contrast enhancement, local distortion of healthy tissue, infiltrating edema adjacent to tumors, destruction and deformation of fiber tracts, and multi-modal MRI contrast of healthy tissue and pathology. The new method synthesizes pathology in multi-modal MRI and diffusion tensor imaging (DTI) by simulating mass effect, warping and destruction of white matter fibers, and infiltration of brain tissues by tumor cells. We generate synthetic contrast enhanced MR images by simulating the accumulation of contrast agent within the brain. The appearance of the the brain tissue and tumor in MRI is simulated by synthesizing texture images from real MR images. The proposed method is able to generate synthetic ground truth and synthesized MR images with tumor and edema that exhibit comparable segmentation challenges to real tumor MRI. Such image data sets will find use in segmentation reliability studies, comparison and validation of different segmentation methods, training and teaching, or even in evaluating standards for tumor size like the RECIST criteria (response evaluation criteria in solid tumors). © 2008 Elsevier B.V. All rights reserved.
Author Keywords
Brain MRI; Diffusion tensor imaging; Gold standard; Ground truth; Segmentation validation; Simulation of tumor infiltration; Tumor simulation
Document Type: Article
Source: Scopus
Preston, J.S.a , Tasdizen, T.b , Terry, C.M.c , Cheung, A.K.c d , Kirby, R.M.e
Using the stochastic collocation method for the uncertainty quantification of drug concentration dDue to depot shape variability
(2009) IEEE Transactions on Biomedical Engineering, 56 (3), art. no. 4694122, pp. 609-620.
a Scientific Computing and Imaging Institute, School of Computing, University of Utah, Salt Lake City, UT 84112, United States
b Scientific Computing and Imaging Institute, Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, UT 84112
c Department of Medicine, University of Utah, Salt Lake City, UT 84112, United States
d Medical Service, Veterans Affairs Salt Lake City Healthcare System, Salt Lake City, UT 84112, United States
e Scientific Computing and Imaging Institute, Department of Mathematics and Bioengineering, University of Utah, Salt Lake City, UT 84112, United States
Abstract
Numerical simulations entail modeling assumptions that impact outcomes. Therefore, characterizing, in a probabilistic sense, the relationship between the variability of model selection and the variability of outcomes is important. Under certain assumptions, the stochastic collocation method offers a computationally feasible alternative to traditional Monte Carlo approaches for assessing the impact of model and parameter variability. We propose a framework that combines component shape parameterization with the stochastic collocation method to study the effect of drug depot shape variability on the outcome of drug diffusion simulations in a porcine model. We use realistic geometries segmented from MR images and employ level-set techniques to create two alternative univariate shape parameterizations. We demonstrate that once the underlying stochastic process is characterized, quantification of the introduced variability is quite straightforward and provides an important step in the validation and verification process. © 2009 IEEE.
Author Keywords
Drug diffusion; Finite-element modeling; Level set; Porcine model; Segmentation; Shape model; Stochastic collocation; Uncertainty quantification
Document Type: Article
Source: Scopus
Cheung, M.R., Krishnan, K.
Interactive Deformation Registration of Endorectal Prostate MRI Using ITK Thin Plate Splines
(2009) Academic Radiology, 16 (3), pp. 351-357.
Department of Radiation Oncology, University of Texas M.D. Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX 77030-4009, United States
Abstract
Rationale and Objectives: Magnetic resonance imaging with an endorectal coil allows high-resolution imaging of prostate cancer and the surrounding normal organs. These anatomic details can be used to direct radiotherapy. However, organ deformation introduced by the endorectal coil makes it difficult to register magnetic resonance images for treatment planning. In this study, plug-ins for the volume visualization software VolView were implemented on the basis of algorithms from the National Library of Medicine's Insight Segmentation and Registration Toolkit (ITK). Materials and Methods: Magnetic resonance images of a phantom simulating human pelvic structures were obtained with and without the endorectal coil balloon inflated. The prostate not deformed by the endorectal balloon was registered to the deformed prostate using an ITK thin plate spline (TPS). This plug-in allows the use of crop planes to limit the deformable registration in the region of interest around the prostate. These crop planes restricted the support of the TPS to the area around the prostate, where most of the deformation occurred. The region outside the crop planes was anchored by grid points. Results: The TPS was more accurate in registering the local deformation of the prostate compared with a TPS variant, the elastic body spline. The TPS was also applied to register an in vivo T2-weighted endorectal magnetic resonance image. The intraprostatic tumor was accurately registered. This could potentially guide the boosting of intraprostatic targets. The source and target landmarks were placed graphically. This TPS plug-in allows the registration to be undone. The landmarks could be added, removed, and adjusted in real time and in three dimensions between repeated registrations. Conclusion: This interactive TPS plug-in allows a user to obtain a high level of accuracy satisfactory to a specific application efficiently. Because it is open-source software, the imaging community will be able to validate and improve the algorithm. © 2009 AUR.
Author Keywords
deformable registration; Insight Segmentation and Registration Toolkit; Prostate cancer; radiotherapy; thin plate spline
Document Type: Article
Source: Scopus
Madden, D.J.a c , Spaniol, J.a , Costello, M.C.a , Bucur, B.a , White, L.E.a , Cabeza, R.b , Davis, S.W.b , Dennis, N.A.b , Provenzale, J.M.a , Huettel, S.A.a
Cerebral white matter integrity mediates adult age differences in cognitive performance
(2009) Journal of Cognitive Neuroscience, 21 (2), pp. 289-302. Cited 5 times.
a Duke University, Medical Center
b Duke University
c Duke University, Medical Center, Durham, NC 27710
Abstract
Previous research has established that age-related decline occurs in measures of cerebral white matter integrity, but the role of this decline in age-related cognitive changes is not clear. To conclude that white matter integrity has a mediating (causal) contribution, it is necessary to demonstrate that statistical control of the white matter-cognition relation reduces the magnitude of age-cognition relation. In this research, we tested the mediating role of white matter integrity, in the context of a task-switching paradigm involving word categorization. Participants were 20 healthy, community-dwelling older adults (60-85 years), and 20 younger adults (18-27 years). From diffusion tensor imaging tractography, we obtained fractional anisotropy (FA) as an index of white matter integrity in the genu and splenium of the corpus callosum and the superior longitudinal fasciculus (SLF). Mean FA values exhibited age-related decline consistent with a decrease in white matter integrity. From a model of reaction time distributions, we obtained independent estimates of the decisional and nondecisional (perceptual-motor) components of task performance. Age-related decline was evident in both components. Critically, age differences in task performance were mediated by FA in two regions: the central portion of the genu, and splenium-parietal fibers in the right hemisphere. This relation held only for the decisional component and was not evident in the nondeci-sional component. This result is the first demonstration that the integrity of specific white matter tracts is a mediator of age-related changes in cognitive performance. © 2008 Massachusetts Institute of Technology.
Document Type: Article
Source: Scopus
Ding, X.-Q.a b , Sun, Y.b , Kruse, B.c , Illies, T.b , Zeumer, H.b , Fiehler, J.b , Lanfermann, H.a
Microstructural callosal abnormalities in normal-appearing brain of children with developmental delay detected with diffusion tensor imaging
(2009) European Radiology, 19 (6), pp. 1537-1543.
a Institute of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Carl-Neuberg-Str. 1, 30625 Hannover, Germany
b Department of Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
c Department of Pediatrics, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
Abstract
Callosal fibres play an important role in psychomotor and cognitive functions. The purpose of this study was to investigate possible microstructural abnormalities of the corpus callosum in children with developmental delay, who have normal conventional brain MR imaging results. Seventeen pediatric patients (aged 1-9 years) with developmental delay were studied. Quantitative T2 and fractional anisotropy FA) values were measured at the genu and splenium of the corpus callosum (CC). Fibre tracking, volumetric determination, as well as fibre density calculations of the CC were also carried out. The results were compared with those of the age-matched healthy subjects. A general elevation of T2 relaxation times (105 ms in patients vs. 95 ms in controls) and reduction of the FA values (0.66 in patients vs. 0.74 in controls) at the genu of the CC were found in patients. Reductions of the fibre numbers (5,464 in patients vs. 8,886 in controls) and volumes (3,415 ml in patients vs. 5,235 ml in controls) of the CC were found only in patients older than 5 years. The study indicates that despite their inconspicuous findings in conventional MRI microstructural brain abnormalities are evident in these pediatric patients suffering from developmental delay. © European Society of Radiology 2009.
Author Keywords
Callosal fibres; Developmental delay; Fibre tracking; Fractional anisotropy
Document Type: Article
Source: Scopus
Yushkevich, P.A.a , Avants, B.B.a , Pluta, J.b , Das, S.a , Minkoff, D.b , Mechanic-Hamilton, D.b , Glynn, S.e , Pickup, S.c , Liu, W.c , Gee, J.C.a , Grossman, M.d , Detre, J.A.b
A high-resolution computational atlas of the human hippocampus from postmortem magnetic resonance imaging at 9.4 T
(2009) NeuroImage, 44 (2), pp. 385-398. Cited 3 times.
a Penn Image Computing and Science Laboratory (PICSL), Department of Radiology, University of Pennsylvania, 3600 Market St., Ste 370, Philadelphia, PA 19104, United States
b Center for Functional Neuroimaging, Departments of Radiology and Neurology, University of Pennsylvania, Philadelphia, PA, United States
c Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States
d Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
e Department of Neurology, University of Michigan, Ann Arbor, MI, United States
Abstract
This paper describes the construction of a computational anatomical atlas of the human hippocampus. The atlas is derived from high-resolution 9.4 Tesla MRI of postmortem samples. The main subfields of the hippocampus (cornu ammonis fields CA1, CA2/3; the dentate gyrus; and the vestigial hippocampal sulcus) are labeled in the images manually using a combination of distinguishable image features and geometrical features. A synthetic average image is derived from the MRI of the samples using shape and intensity averaging in the diffeomorphic non-linear registration framework, and a consensus labeling of the template is generated. The agreement of the consensus labeling with manual labeling of each sample is measured, and the effect of aiding registration with landmarks and manually generated mask images is evaluated. The atlas is provided as an online resource with the aim of supporting subfield segmentation in emerging hippocampus imaging and image analysis techniques. An example application examining subfield-level hippocampal atrophy in temporal lobe epilepsy demonstrates the application of the atlas to in vivo studies. © 2008 Elsevier Inc. All rights reserved.
Document Type: Article
Source: Scopus
Shamir, R.R.a , Joskowicz, L.a , Spektor, S.b , Shoshan, Y.b
Localization and registration accuracy in image guided neurosurgery: A clinical study
(2009) International Journal of Computer Assisted Radiology and Surgery, 4 (1), pp. 45-52. Cited 1 time.
a School of Engineering and Computer Science, The Hebrew University of Jerusalem, Givat Ram Campus, 91904 Jerusalem, Israel
b Department of Neurosurgery, School of Medicine, Hadassah University Hospital, Jerusalem, Israel
Abstract
Purpose: To measure and compare the clinical localization and registration errors in image-guided neurosurgery, with the purpose of revising current assumptions. Materials and methods: Twelve patients who underwent brain surgeries with a navigation system were randomly selected. A neurosurgeon localized and correlated the landmarks on preoperative MRI images and on the intraoperative physical anatomy with a tracked pointer. In the laboratory, we generated 612 scenarios in which one landmark pair was defined as the target and the remaining ones were used to compute the registration transformation. Four errors were measured: (1) fiducial localization error (FLE); (2) target registration error (TRE); (3) fiducial registration error (FRE); (4) Fitzpatrick's target registration error estimation (F-TRE). We compared the different errors and computed their correlation. Results: The image and physical FLE ranges were 0.5-2.0 and 1.6-3.0 mm, respectively. The measured TRE, FRE and F-TRE were 4.1 ± 1.6, 3.9 ± 1.2, and 3.7 ± 2.2 mm, respectively. Low correlations of 0.19 and 0.37 were observed between the FRE and TRE and between the F-TRE and the TRE, respectively. The differences of the FRE and F-TRE from the TRE were 1.3 ± 1.0 mm (max = 5.5 mm) and 1.3 ± 1.2 mm (max = 7.3 mm), respectively. Conclusion: Contrary to common belief, the FLE presents significant variations. Moreover, both the FRE and the F-TRE are poor indicators of the TRE in image-to-patient registration. © CARS 2008.
Author Keywords
Image-guided navigation; Localization error; Neurosurgery; Registration error
Document Type: Article
Source: Scopus
Qiao, C.a , Li, J.a , Zheng, H.a b , Bogan, J.c , Li, J.a , Yuan, Z.a , Zhang, C.b , Bogan, D.c , Kornegay, J.c d , Xiao, X.a c
Hydrodynamic limb vein injection of adeno-associated virus serotype 8 vector carrying canine myostatin propeptide gene into normal dogs enhances muscle growth
(2009) Human Gene Therapy, 20 (1), pp. 1-10. Cited 1 time.
a Division of Molecular Pharmaceutics, University of North Carolina School of Pharmacy, Chapel Hill, NC 27599, United States
b Department of Neurology, First Affiliated Hospital, Sun Yat-sen University, Guangzhou 510080, China
c Gene Therapy Center, University of North Carolina School of Medicine, Chapel Hill, NC 27599, United States
d Department of Pathology and Laboratory Medicine, Department of Neurology, University of North Carolina School of Medicine, Chapel Hill, NC 27599, United States
Abstract
Inhibition or blockade of myostatin, a negative growth factor of skeletal muscle, enhances muscle growth and therefore is considered a promising strategy for the treatment of muscle-wasting diseases such as the muscular dystrophies. Previously, we showed that myostatin blockade in both normal and dystrophin-deficient mdx mice by systemic delivery of the myostatin propeptide (MPRO) gene by an adeno-associated virus serotype 8 (AAV8) vector could enhance muscle growth and ameliorate dystrophic lesions. Here, we further investigate whether the muscle growth effect of myostatin blockade can be achieved in dogs by gene transfer. First, we cloned the canine MPRO gene, packaged it in the AAV8 vector, and showed robust muscle-enhancing effects after systemic delivery into neonatal mice. This vector was then further tested in two 3-month-old normal dogs (weighing 9.7 and 6.3 kg). The vector was delivered to one limb by hydrodynamic vein injection, and the contralateral limb served as a control. The delivery procedure was safe, without discernible adverse effects. AAV vector DNA and MPRO gene expression were detected by quantitative polymerase chain reaction, Western blotting, and immunofluorescence staining of muscle biopsies. Overexpression of MPRO resulted in enhanced muscle growth without a cytotoxic T lymphocytic immune response, as evidenced by larger myofibers in multiple muscles, increased muscle volume determined by magnetic resonance imaging, and the lack of CD4+ and CD8+ T cell infiltration in the vector-injected limbs. Our preliminary study thus supports further investigation of this therapeutic strategy in the dystrophin-deficient golden retriever muscular dystrophy dog model. © Copyright 2009, Mary Ann Liebert, Inc.
Document Type: Article
Source: Scopus
Sherbondy, A.J.a d , Dougherty, R.F.b , Napel, S.c , Wandell, B.A.b
Identifying the human optic radiation using diffusion imaging and fiber tractography
(2008) Journal of Vision, 8 (10), art. no. 12, . Cited 1 time.
a Department of Electrical Engineering, Stanford University, Stanford, CA, United States
b Department of Psychology, Stanford University, Stanford, CA, United States
c Department of Radiology, Stanford University, Stanford, CA, United States
d 450 Serra Mall, Stanford, CA 94305, United States
Abstract
Measuring the properties of the white matter pathways from retina to cortex in the living human brain will have many uses for understanding visual performance and guiding clinical treatment. For example, identifying the Meyer's loop portion of the optic radiation (OR) has clinical significance because of the large number of temporal lobe resections. We use diffusion tensor imaging and fiber tractography (DTI-FT) to identify the most likely pathway between the lateral geniculate nucleus (LGN) and the calcarine sulcus in sixteen hemispheres of eight healthy volunteers. Quantitative population comparisons between DTI-FT estimates and published postmortem dissections match with a spatial precision of about 1 mm. The OR can be divided into three bundles that are segmented based on the direction of the fibers as they leave the LGN: Meyer's loop, central, and direct. The longitudinal and radial diffusivities of the three bundles do not differ within the measurement noise; there is a small difference in the radial diffusivity between the right and left hemispheres. We find that the anterior tip of Meyer's loop is 28 ± 3 mm posterior to the temporal pole, and the population range is 1 cm. Hence, it is important to identify the location of this bundle in individual subjects or patients. © ARVO.
Author Keywords
Diffusion imaging; Fiber tractography; Lateral geniculate nucleus; Optic radiation
Document Type: Article
Source: Scopus
Gilmore, J.H.a , Smith, L.C.a , Wolfe, H.M.b , Hertzberg, B.S.e , Smith, J.K.c , Chescheir, N.C.f , Evans, D.D.a , Kang, C.d , Hamer, R.M.a d , Lin, W.c , Gerig, G.g
Prenatal Mild Ventriculomegaly Predicts Abnormal Development of the Neonatal Brain
(2008) Biological Psychiatry, 64 (12), pp. 1069-1076.
a Schizophrenia Research Center, the Department of Psychiatry, School of Medicine, Chapel Hill, United States
b Department of Obstetrics and Gynecology, School of Medicine, University of North Carolina, Chapel Hill, United States
c Department of Radiology, School of Medicine, University of North Carolina, Chapel Hill, United States
d Department of Biostatistics, School of Medicine, University of North Carolina, Chapel Hill, United States
e Department of Radiology, Duke University Medical Center, Durham, NC, United States
f Department of Obstetrics and Gynecology, Vanderbilt School of Medicine, Nashville, TN, United States
g Department of Scientific Computing and Imaging, University of Utah, Salt Lake City, UT, United States
Abstract
Background: Many psychiatric and neurodevelopmental disorders are associated with mild enlargement of the lateral ventricles thought to have origins in prenatal brain development. Little is known about development of the lateral ventricles and the relationship of prenatal lateral ventricle enlargement with postnatal brain development. Methods: We performed neonatal magnetic resonance imaging on 34 children with isolated mild ventriculomegaly (MVM; width of the atrium of the lateral ventricle ≥ 1.0 cm) on prenatal ultrasound and 34 age- and sex-matched control subjects with normal prenatal ventricle size. Lateral ventricle and cortical gray and white matter volumes were assessed. Fractional anisotropy (FA) and mean diffusivity (MD) in corpus callosum and corticospinal white matter tracts were determined obtained using quantitative tractography. Results: Neonates with prenatal MVM had significantly larger lateral ventricle volumes than matched control subjects (286.4%; p < .0001). Neonates with MVM also had significantly larger intracranial volumes (ICV; 7.1%, p = .0063) and cortical gray matter volumes (10.9%, p = .0004) compared with control subjects. Diffusion tensor imaging tractography revealed a significantly greater MD in the corpus callosum and corticospinal tracts, whereas FA was significantly smaller in several white matter tract regions. Conclusions: Prenatal enlargement of the lateral ventricle is associated with enlargement of the lateral ventricles after birth, as well as greater gray matter volumes and delayed or abnormal maturation of white matter. It is suggested that prenatal ventricle volume is an early structural marker of altered development of the cerebral cortex and may be a marker of risk for neuropsychiatric disorders associated with ventricle enlargement. © 2008 Society of Biological Psychiatry.
Author Keywords
Autism; cortex; diffusion tensor imaging; lateral ventricle; magnetic resonance imaging; schizophrenia; ultrasound
Document Type: Article
Source: Scopus
Poon, M.a , Hamarneh, G.b , Abugharbieh, R.a
Efficient interactive 3D Livewire segmentation of complex objects with arbitrary topology
(2008) Computerized Medical Imaging and Graphics, 32 (8), pp. 639-650. Cited 1 time.
a Biomedical Signal and Image Computing Laboratory, University of British Columbia, Vancouver, V6T 1Z4, Canada
b Medical Image Analysis Laboratory, Simon Fraser University, Burnaby, V5A 1S6, Canada
Abstract
We present a novel interactive method based on a 3D Livewire approach for segmenting complex objects of arbitrary topologies. Our proposed technique automatically and seamlessly handles objects with branchings, concavities, protrusions, and non-spherical topologies with minimal user-input. Given sparse interactively segmented contours on orthogonal slices, our proposed method determines Livewire seedpoints on all slices in the third orthogonal direction, which are used to mimic user-guided segmentation. In doing so, our method pre-processes these points to increase algorithm robustness, and uses a novel seedpoint sorting method using ideas from L-system's Turtle algorithm. Moreover, we present a segmentation tool based on our proposed framework and demonstrate the robustness of our approach on real medical data. Results highlight the superior performance of the proposed method with validation tests on synthetic and real MRI and CT data, with segmentation reproducibility exceeding 95% and segmentation task time decreasing to less than 20% when compared to performing 2D Livewire on each volume slice. © 2008 Elsevier Ltd. All rights reserved.
Author Keywords
3D segmentation; Interactive segmentation; Livewire; Medical imaging; User-interaction
Document Type: Article
Source: Scopus
Liu, J., Su, H., Nowinski, W.L.
A hybrid approach for segmentation of anatomic structures in medical images
(2008) International Journal of Computer Assisted Radiology and Surgery, 3 (3-4), pp. 213-219.
Biomedical Imaging Laboratory, Singapore BioImaging Consortium, Agency for Science, Technology and Research, Singapore, Singapore
Abstract
Objective: We propose a hybrid interactive approach for the segmentation of anatomic structures in medical images with higher accuracy at lower user interaction cost. Materials and methods: Eighteen brain MR scans from the Internet Brain Segmentation Repository are used for brain structure segmentation. A MR scan and a CT scan of an old female are used for orbital structure segmentation. The proposed approach combines shape-based interpolation, radial basis function (RBF)-based warping and model-based segmentation. With this approach, to segment a structure in a 3D image, we first delineate the structure in several slices using interactive methods, and then use shape-based interpolation to automatically generate an initial 3D model of the structure from the segmented slices. To refine the initial model, we specify a set of additional points on the structure boundary in the image, and use a RBF to warp the model so that it passes the specified points. Finally, we adopt a point-anchored active surface approach to further deform the model for a better fitting of the model with its corresponding structure in image. Results: Two brain structures and 15 orbital structures are segmented. For each structure, it needs only to semi- automatically segment three to five 2D slices and specify two to nine additional points on the structure boundary. The time cost for each structure is about 1-3 min. The overlap ratio of the segmentation results and the ground truth is higher than 96%. Conclusion: The proposed method for the segmentation of anatomic structure achieved higher accuracy at lower user interaction cost, and therefore promising in many applications such as surgery planning and simulation, atlas construction, and morphometric analysis of anatomic structures. © CARS 2008.
Author Keywords
Anatomic structure; Image segmentation; Point-anchored active surface; Radial basis function-based warping; Shape interpolation
Document Type: Article
Source: Scopus
He, Q.a , Duan, Y.a , Yin, X.b , Gu, X.b , Karsch, K.a , Miles, J.c
Detecting thalamic abnormalities in autism using cylinder conformal mapping
(2008) Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5359 LNCS (PART 2), pp. 743-751.
a Department of Computer Science, University of Missouri-Columbia, Columbia, MO 65211, United States
b State University of New York at Stony Brook, Stony Brook, NY 11794, United States
c Thompson Center for Autism, University of Missouri-Columbia, Columbia, MO 65211, United States
Abstract
A number of studies have documented that autism has a neurobiological basis, but the anatomical extent of these neurobiological abnormalities is largely unknown. In this paper, we applied advanced computational techniques to extract 3D surface models of the thalamus and subsequently analyze highly localized shape variations in a homogeneous group of autism children. In particular, a new conformal parameterization for high genus surfaces is applied in our shape analysis work, which maps the surfaces onto a cylinder domain. Surface matching among different individual meshes is achieved by re-triangulating each mesh according to the template. Children with autism and their controls are compared, and statistical significant abnormalities in thalamus of autism are detected. © 2008 Springer Berlin Heidelberg.
Document Type: Conference Paper
Source: Scopus
Osareh, A., Shadgar, B.
A modified geometric-based active contour model for lung segmentation in magnetic resonance images
(2008) Journal of Medical and Biological Engineering, 28 (4), pp. 211-221.
Department of Computer Science, Faculty of Engineering, Shahid Chamran University, Ahvaz 61355, Iran
Abstract
Segmentation of medical images is very important for clinical research and diagnosis, leading to a requirement for robust automated methods. An essential part of a successful radiotherapy planning system for breast cancer treatment is the accurate segmentation of target organs at risk, such as lungs. Distinguishing of the lung cavities is not trivial due to largely changing lung shapes, low contrast and poorly defined boundaries even in the absence of prominent neighboring structures. In this study, we address the lung segmentation problem in pulmonary magnetic resonance imaging and propose an automated method based on a robust region-aided geometric snake with a modified diffused region force into the standard geometric model definition. (This extra region force which is created by Fuzzy C-Means algorithm gives the snake a global complementary view of the lung boundary information within the image. Along with the local gradient flow, it helps detect fuzzy boundaries and overcome noisy regions in our MR images.) The proposed method has been successful in segmenting the lungs in every slice of 30 magnetic resonance images with 80 consecutive slices in each image. We present results by comparing our automatic method to manually segmented lung cavities provided by an expert radiologist and with those of previous works, showing encouraging results and high robustness of our approach.
Author Keywords
Breast cancer; Fuzzy C-means; Geometric active contour; Radiotherapy treatment planning; Template matching
Document Type: Article
Source: Scopus
Lopes, D.S.a , Martins, J.A.C.a , Pires, E.B.a , Rodrigues, L.B.b c , De Las Casas, E.B.d , Faleiros, R.R.d
A geometric modeling pipeline for bone structures based on computed tomography data: A veterinary study
(2008) Proceedings of VIPIMAGE 2007 - 1st ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing, pp. 217-222.
a Instituto Superior Técnico, ICIST, Technical University of Lisbon, Lisbon, Portugal
b State University of Bahia Southwest, Campus of Itapetinga, Itapetinga, Brazil
c Mechanical Engineering Graduate Program, Federal University of Minas Gerais, Belo Horizonte, Brazil
d Federal University of Minas Gerais, Belo Horizonte, Brazil
Abstract
Computed Tomography (CT) is an imaging modality that reveals the inner parts of a body in a non-invasive fashion, providing the geometrical data suitable for the development of three-dimensional (3D) models. Due to the high signal contrast between hard and soft tissues, CT images are appropriate for bone structure modeling, visualization and manufacturing. In this paper, a mesh-based geometric modeling pipeline, capable of generating accurate surface meshes of bone structures for visualization and prototyping, is presented. A CAD-based modeling pipeline is also presented to provide computational finite element meshes for bone structures. The pipeline is composed by several software tools, mainly freeware, each with specific functionalities in the overall modeling scheme: image restoration and enhancement, image segmentation, mesh generation and adjustment. A veterinary application is considered aiming at the development of an intramedullary interlocking nail to be used for treatment of fractures in long bones of large animals. © 2008 Taylor & Francis Group.
Document Type: Conference Paper
Source: Scopus
Knickmeyer, R.C.a , Gouttard, S.b , Kang, C.c , Evans, D.a , Wilber, K.d , Smith, J.K.d , Hamer, R.M.a c , Lin, W.d , Gerig, G.b , Gilmore, J.H.a e
A structural MRI study of human brain development from birth to 2 years
(2008) Journal of Neuroscience, 28 (47), pp. 12176-12182. Cited 2 times.
a Department of Psychiatry, University of North Carolina, Chapel Hill, NC 27599-7160, United States
b Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT 84112, United States
c Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599-7420, United States
d Department of Radiology, University of North Carolina, Chapel Hill, NC 27599-7510, United States
e Department of Psychiatry, 7025 Neurosciences Hospital, University of North Carolina, Chapel Hill, NC 27599-7160, United States
Abstract
Brain development in the first 2 years after birth is extremely dynamic and likely plays an important role in neurodevelopmental disorders, including autism and schizophrenia. Knowledge regarding this period is currently quite limited. We studied structural brain development in healthy subjects from birth to 2. Ninety-eight children received structural MRI scans on a Siemens head-only 3T scanner with magnetization prepared rapid gradient echo T1-weighted, and turbo spin echo, dual-echo (proton density and T2 weighted) sequences: 84 children at 2-4 weeks, 35 at 1 year and 26 at 2 years of age. Tissue segmentation was accomplished using a novel automated approach. Lateral ventricle, caudate, and hippocampal volumes were also determined. Total brain volume increased 101% in the first year, with a 15% increase in the second. The majority of hemispheric growth was accounted for by gray matter, which increased 149% in the first year; hemispheric white matter volume increased by only 11%. Cerebellum volume increased 240% in the first year. Lateral ventricle volume increased 280% in the first year, with a small decrease in the second. The caudate increased 19% and the hippocampus 13% from age 1 to age 2. There was robust growth of the human brain in the first two years of life, driven mainly by gray matter growth. In contrast, white matter growth was much slower. Cerebellum volume also increased substantially in the first year of life. These results suggest the structural underpinnings of cognitive and motor development in early childhood, as well as the potential pathogenesis of neurodevelopmental disorders. Copyright © 2008 Society for Neuroscience.
Author Keywords
Brain development; Caudate; Children; Cortex; Hippocampus; Magnetic resonance imaging
Document Type: Article
Source: Scopus
Jianwu, D.a , Yangping, W.a , Sha, L.b , Zhengping, Z.c
Heavy-ion radiotherapy treatment planning system and medical image processing algorithm used in it
(2008) 4th IEEE Conference on Automation Science and Engineering, CASE 2008, art. no. 4626514, pp. 726-731.
a School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou, 730070, China
b Lanzhou Generation Hospital Lanzhou Command, Lanzhou, 730050, China
c Department of Computer, Lanzhou City University, Lanzhou, 730070, China
Abstract
As heavy-ion beam can generate a Bragg peak and the radiation dose can be easily concentrated on the tumor volume by utilizing the peak, nowadays heavy-ion radiotherapy is considered as a most powerful remedy for tumors. To make a conformal treatment plan, radiation treatment planning system (RTFS) is an important and necessary component in any radiation therapy. In our study, a heavy-ion RTPS has been developed for high-energy heavy-ion accelerator HIRFL-CSR in China and the accelerator can location Bragg peak on deep-seated tumor. The paper analyses the requirement of the software system, designs the framework, introduces the module function and shows the data flow of the treatment planning software system. Meanwhile, the paper has developed medical image fusion algorithm based on fuzzy-RBFNN (radial basis function neural networks) to overcome the blurry images. Improved interactive image segmentation algorithm and 3-D reconstruction algorithm have been developed too in the software system and achieved outstanding outcome. ©2008 IEEE.
Document Type: Conference Paper
Source: Scopus
Santos, M.I.a b c , Tuzlakoglu, K.a b d , Fuchs, S.c , Gomes, M.E.a b , Peters, K.e , Unger, R.E.c , Piskin, E.d , Reis, R.L.a b , Kirkpatrick, C.J.c
Endothelial cell colonization and angiogenic potential of combined nano- and micro-fibrous scaffolds for bone tissue engineering
(2008) Biomaterials, 29 (32), pp. 4306-4313. Cited 5 times.
a 3B's Research Group - Biomaterials, Biodegradables and Biomimetics, Department of Polymer Engineering, Campus de Gualtar, 4710-057 Braga, Portugal
b IBB - Institute for Biotechnology and Bioengineering, PT Government Associated Laboratory, Braga, Portugal
c Institute of Pathology, Johannes Gutenberg University Mainz, Langenbeckstrasse 1, Mainz, 55101, Germany
d Hacettepe University, Chemical Engineering Department, Bioengineering Division, Beytepe, 06532 Ankara, Turkey
e Department of Cell Biology, Junior Research Group, Medical Faculty, Schillingallee 69, 18057 Rostock, Germany
Abstract
Presently the majority of tissue engineering approaches aimed at regenerating bone relies only on post-implantation vascularization. Strategies that include seeding endothelial cells (ECs) on biomaterials and promoting their adhesion, migration and functionality might be a solution for the formation of vascularized bone. Nano/micro-fiber-combined scaffolds have an innovative structure, inspired by extracellular matrix (ECM) that combines a nano-network, aimed to promote cell adhesion, with a micro-fiber mesh that provides the mechanical support. In this work we addressed the influence of this nano-network on growth pattern, morphology, inflammatory expression profile, expression of structural proteins, homotypic interactions and angiogenic potential of human EC cultured on a scaffold made of a blend of starch and poly(caprolactone). The nano-network allowed cells to span between individual micro-fibers and influenced cell morphology. Furthermore, on nano-fibers as well as on micro-fibers ECs maintained the physiological expression pattern of the structural protein vimentin and PECAM-1 between adjacent cells. In addition, ECs growing on the nano/micro-fiber-combined scaffold were sensitive to pro-inflammatory stimulus. Under pro-angiogenic conditions in vitro, the ECM-like nano-network provided the structural and organizational stability for ECs' migration and organization into capillary-like structures. The architecture of nano/micro-fiber-combined scaffolds elicited and guided the 3D distribution of ECs without compromising the structural requirements for bone regeneration. © 2008 Elsevier Ltd. All rights reserved.
Author Keywords
Bone tissue engineering; Endothelial cells; Nano-fibers; Starch-based scaffolds; Vascularization
Document Type: Article
Source: Scopus
Morra, J.H.a , Tu, Z.a , Apostolova, L.G.a b , Green, A.E.a b , Avedissian, C.a , Madsen, S.K.a , Parikshak, N.a , Hua, X.a , Toga, A.W.a , Jack Jr., C.R.c , Weiner, M.W.d e , Thompson, P.M.a
Validation of a fully automated 3D hippocampal segmentation method using subjects with Alzheimer's disease mild cognitive impairment, and elderly controls
(2008) NeuroImage, 43 (1), pp. 59-68. Cited 7 times.
a Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, Los Angeles, CA, United States
b Department of Neurology, UCLA School of Medicine, Los Angeles, CA, United States
c Mayo Clinic College of Medicine, Rochester, MN, United States
d Department of Radiology, UC San Francisco, San Francisco, CA, United States
e Department of Medicine and Psychiatry, UC San Francisco, San Francisco, CA, United States
Abstract
We introduce a new method for brain MRI segmentation, called the auto context model (ACM), to segment the hippocampus automatically in 3D T1-weighted structural brain MRI scans of subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI). In a training phase, our algorithm used 21 hand-labeled segmentations to learn a classification rule for hippocampal versus non-hippocampal regions using a modified AdaBoost method, based on ∼ 18,000 features (image intensity, position, image curvatures, image gradients, tissue classification maps of gray/white matter and CSF, and mean, standard deviation, and Haar filters of size 1 × 1 × 1 to 7 × 7 × 7). We linearly registered all brains to a standard template to devise a basic shape prior to capture the global shape of the hippocampus, defined as the pointwise summation of all the training masks. We also included curvature, gradient, mean, standard deviation, and Haar filters of the shape prior and the tissue classified images as features. During each iteration of ACM - our extension of AdaBoost - the Bayesian posterior distribution of the labeling was fed back in as an input, along with its neighborhood features as new features for AdaBoost to use. In validation studies, we compared our results with hand-labeled segmentations by two experts. Using a leave-one-out approach and standard overlap and distance error metrics, our automated segmentations agreed well with human raters; any differences were comparable to differences between trained human raters. Our error metrics compare favorably with those previously reported for other automated hippocampal segmentations, suggesting the utility of the approach for large-scale studies. © 2008 Elsevier Inc. All rights reserved.
Document Type: Article
Source: Scopus
Van Norden, A.G.W.a , Fick, W.F.a , De Laat, K.F.a , Van Uden, I.W.M.a , Van Oudheusden, L.J.B.a , Tendolkar, I.b , Zwiers, M.P.c , De Leeuw, F.E.a d
Subjective cognitive failures and hippocampal volume in elderly with white matter lesions
(2008) Neurology, 71 (15), pp. 1152-1159. Cited 2 times.
a Department of Neurology, Radboud University Nijmegen Medical Centre, Donders Institute for Brain, Cognition, and Behaviour, Netherlands
b Department of Psychiatry, Radboud University Nijmegen Medical Centre, Donders Institute for Brain, Cognition, and Behaviour, Netherlands
c FC Donders Centre for Cognitive Neuroimaging, Radboud University Nijmegen, Netherlands
d Department of Neurology, Radboud University, Nijmegen Medical Centre, Reinier Postlaan 4, 6500 HB Nijmegen, Netherlands
Abstract
BACKGROUND: Subjective cognitive failures (SCF) and subjective memory failures (SMF) have been reported to be an early predictor of Alzheimer disease (AD) and have been attributed to white matter lesions (WML). Since AD is characterized by hippocampal degeneration, it is surprising that its relation with hippocampal atrophy has been investigated only sparsely. Previous studies on this are rare, limited in sample size, and did not adjust for WML. OBJECTIVE: To determine the relation between SCF and hippocampal volume in strata of objective cognitive performance among elderly without dementia with incidental WML. METHODS: The Radboud University Nijmegen Diffusion tensor and MRI Cohort study is a prospective cohort study among 503 subjects with WML aged between 50 and 85 years. All subjects underwent FLAIR and T1 MRI scanning. The amount of SCF and SMF was rated by the Cognitive Failure Questionnaire. Cognitive function was assessed by a cognitive screening battery. Volumetric measures of hippocampus and WML were manually performed. We assessed the relation between hippocampal volume and SCF and SMF adjusted for age, sex, education, depression, intracranial volume, and WML volume. RESULTS: Subjects with SCF and SMF had lower hippocampal volumes than those without (p = 0.01 and p = 0.02). This was most noteworthy in subjects with good objective cognitive performance (ptrend = 0.007 and ptrend = 0.03), and not in those with poor objective cognitive performance. CONCLUSION: Subjective cognitive failures (SCF) are associated with lower hippocampal volume, even in subjects without objective cognitive impairment and independent of white matter lesions. SCF has a radiologic detectable pathologic-anatomic substrate. © 2008 by AAN Enterprises, Inc.
Document Type: Article
Source: Scopus
Lenič, M., Cigale, B., Potočnik, B., Zazula, D.
Fast segmentation of ovarian ultrasound volumes using support vector machines and sparse learning sets
(2008) Studies in Computational Intelligence, 142, pp. 95-105.
Faculty of Electrical Engineering and Computer Science, University of Maribor, Smetanova 17, Maribor 2000, Slovenia
Abstract
Ovarian ultrasound imaging has recently drawn attention because of the improved ultrasound-based diagnostic methods and because of its application to in-vitro fertilisation and prediction of women's fertility. Modern ultrasound devices enable frequent examinations and sophisticated built-in image processing options. However, precise detection of different ovarian structures, in particular follicles and their growth still need additional, mainly off-line processing with highly specialised algorithms. Manual annotation of a whole 3D ultrasound volume consisting of 100 and more slices, i.e. 2D ultrasound images, is a tedious task even when using handy, computer-assisted segmentation tools. Our paper reveals how an application of support vector machines (SVM) can ease the follicle detection by speeding up the learning and annotation processes at the same time. An iterative SVM approach is introduced using training on sparse learning sets only. The recognised follicles are compared to the referential expert readings and to the results obtained after learning on the entire annotated 3D ovarian volume. © 2008 Springer-Verlag Berlin Heidelberg.
Author Keywords
Fast learning; Iterative SVM; Medical image segmentation; Ovarian follicles; Sparse learning sets; Support vector machines (SVM); Ultrasound imaging
Document Type: Article
Source: Scopus
Morra, J.H.a , Tu, Z.a , Apostolova, L.G.a b , Green, A.E.a b , Avedissian, C.a , Madsen, S.K.a , Parikshak, N.a , Hua, X.a , Toga, A.W.a , Jack Jr., C.R.c , Schuff, N.d , Weiner, M.W.d e , Thompson, P.a
Mapping hippocampal degeneration in 400 subjects with a novel automated segmentation approach
(2008) 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Proceedings, ISBI, art. no. 4541001, pp. 336-339. Cited 1 time.
a Laboratory of NeuroImaging, UCLA School of Medicine, Los Angeles, CA, United States
b Dept. of Neurology, UCLA School of Medicine, Los Angeles, CA, United States
c Mayo Clinic College of Medicine, Rochester, MN, United States
d Dept. Radiology, UC San Francisco, San Francisco, CA, United States
e Dept. Medicine and Psychiatry, UC San Francisco, San Francisco, CA, United States
Abstract
We automatically segmented the hippocampus in 400 brain MRI scans from the Alzheimer's Disease (AD) Neuroimaging Initiative, combining AdaBoost with a novel model, the Auto Context Model (ACM). Trained on 21 hand-labeled segmentations, ACM created binary hippocampus maps in 100 controls, 200 with mild cognitive impairment (MCI), and 100 AD subjects, (age: 75.8+/-6.6SD). A radial atrophy mapping technique computed average parametric surface models and local statistics of atrophy. We visualized correlations between regional atrophy and diagnosis (MCI v. controls: p = 0.008; MCI v. AD: p = 0.001), mini-mental state exam scores, and clinical dementia rating scores (CDR; all p < 0.0001, corrected). Based on false discovery rate curves in gradually reduced samples, 40 subjects were sufficient to correlate atrophy and CDR scores; MCI and AD were distinguishable with N = 304. ©2008 IEEE.
Author Keywords
AdaBoost; Alzheimer's disease; Hippocampal segmentation; Magnetic resonance imaging
Document Type: Conference Paper
Source: Scopus
Fürnstahl, P.a , Fuchs, T.b , Schweizer, A.c , Nagy, L.c , Sźekely, G.a , Harders, M.a
Automatic and robust forearm segmentation using graph cuts
(2008) 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Proceedings, ISBI, art. no. 4540936, pp. 77-80.
a Computer Vision Laboratory, ETH Zurich, Zurich, Switzerland
b Institute of Computational Science, ETH Zurich, Zurich, Switzerland
c Department of Orthopedic Surgery, University Hospital Balgrist, Zurich, Switzerland
Abstract
The segmentation of bones in computed tomography (CT) images is an important step for the simulation of forearm bone motion, since it allows to include patient specific anatomy in a kinematic model. While the identification of the bone diaphysis is straightforward, the segmentation of bone joints with weak, thin, and diffusive boundaries is still a challenge. We propose a graph cut segmentation approach that is particularly suited to robustly segment joints in 3-d CT images. We incorporate knowledge about intensity, bone shape and local structures into a novel energy function. Our presented framework performs a simultaneous segmentation of both forearm bones without any user interaction. ©2008 IEEE.
Author Keywords
Bone; Forearm; Graph cut; Segmentation
Document Type: Conference Paper
Source: Scopus
Lin, X.a , Young, A.a b , Cowan, B.b
Localization and atlas-based segmentation of the heart from cardiac MR images: Validation with a large clinical trial
(2008) 2nd International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2008, art. no. 4535792, pp. 2319-2322.
a Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
b Auckland MRI Research Group, University of Auckland, Auckland, New Zealand
Abstract
This paper presents an automatic method to find and segment the boarders of the left and right ventricles (LV and RV) from the middle short axis (SA) slice of a functional cardiac MRI study. The segmentation is implemented using a new atlas-based registration framework which is able to integrate boundary, intensity and anatomical information. The method is shown to be accurate, robust and reliable in a clinical trial of 330 patients with a range of cardiac and vascular disease. The method failed in only two cases, and showed high agreement with expert observers in the remaining 328. © 2008 IEEE.
Author Keywords
Atlas-based; Automated; Cardiac MRI; Endocardial; Epicardial; Left and right ventricle; Registration; Segmentation
Document Type: Conference Paper
Source: Scopus
Megali, G.a , Ferrari, V.a , Freschi, C.a , Morabito, B.a , Cavallo, F.a , Turini, G.a , Troia, E.a , Cappelli, C.a , Pietrabissa, A.a , Tonet, O.b , Cuschieri, A.b , Dario, P.b , Mosca, F.a
EndoCAS navigator platform: A common platform for computer and robotic assistance in minimally invasive surgery
(2008) International Journal of Medical Robotics and Computer Assisted Surgery, 4 (3), pp. 242-251. Cited 1 time.
a EndoCAS Center, Università di Pisa, Via Paradisa 2, 56125 Pisa, Italy
b CRIM Lab., Scuola Superiore Sant'Anna, Pisa, Italy
Abstract
Background: Computer-assisted surgery (CAS) systems are currently used in only a few surgical specialties: ear, nose and throat (ENT), neurosurgery and orthopaedics. Almost all of these systems have been developed as dedicated platforms and work on rigid anatomical structures. The development of augmented reality systems for intra-abdominal organs remains problematic because of the anatomical complexity of the human peritoneal cavity and especially because of the deformability of its organs. The aim of the present work was to develop and implement a highly modular platform (targeted for minimally invasive laparoscopic surgery) generally suitable for CAS, and to produce a prototype for demonstration of its potential clinical application and use in laparoscopic surgery. Methods: In this paper we outline details of a platform integrating several aspects of CAS and medical robotics into a modular open architecture: the EndoCAS navigator platform, which integrates all the functionalities necessary for provision of computer-based assistance to surgeons during all the management phases (diagnostic work-up, planning and intervention). A specific application for computer-assisted laparoscopic procedures has been developed on the basic modules of the platform. The system provides capabilities for three-dimensional (3D) surface model generation, 3D visualization, intra-operative registration, surgical guidance and robotic assistance during laparoscopic surgery. The description of specific modules and an account of the initial clinical experience with the system are reported. Results: We developed a common platform for computer assisted surgery and implemented a system for intraoperative laparoscopic navigation. The preliminary clinical trials and feedback from the surgeons on its use in laparoscopic surgery have been positive, although experience has been limited to date. Conclusions: We have successfully developed a system for computer-assisted technologies for use in laparoscopic surgery and demonstrated, by early clinical trials, that the introduction of these technologies in operative laparoscopy, even though they are not yet sufficiently accurate (from an engineering viewpoint) for surgical treatment of intra-abdominal disease, brings added benefits to the execution of interventions by surgeons and hence represents concrete on-going progress in interventional technology. Copyright © 2008 John Wiley & Sons, Ltd.
Author Keywords
Computer-assisted surgery; Image-guided surgical navigation; Minimally invasive surgery
Document Type: Article
Source: Scopus
Costa, A.L.F., Yasuda, C.L., Appenzeller, S., Lopes, S.L.P.C., Cendes, F.
Comparison of conventional MRI and 3D reconstruction model for evaluation of temporomandibular joint
(2008) Surgical and Radiologic Anatomy, 30 (8), pp. 663-667.
Laboratory of Neuroimaging, Department of Neurology, University of Campinas, Cidade Universitaria Zeferino Vaz, Campinas, SP 13083970, Brazil
Abstract
The aim of this work was to define the diagnostic value of a method for 3D reconstruction of MRI images for the assessment of temporomandibular joint. Sixty subjects, 42 diagnosed with unilateral temporomandibular disorders (TMD) with disc displacement and 18 without signs or symptoms of TMD (control group) were included. All subjects had both temporomandibular joints scanned by MRI. Three-dimensional imaging reconstructions of temporomandibular joint were generated by segmentation software, allowing visualization of the components of temporomandibular joint (articular disc, condyle and temporal bone) on arbitrary planes. Disc displacement was observed in 83% of 3D reconstruction and 81% of conventional MRI. The agreement between 3D diagnosis and MRI findings was significant and high. The present analysis suggested that 3D reconstruction is a useful and accurate method for the assessment of the temporomandibular joint in TMD ID. © Springer-Verlag 2008.
Author Keywords
Magnetic resonance imaging; Temporomandibular articular disc; Temporomandibular joint; Three-dimensional image; Three-dimensional reconstruction
Document Type: Article
Source: Scopus
Ding, X.-Q.a b c , Sun, Y.a , Braaß, H.a , Illies, T.a , Zeumer, H.a , Lanfermann, H.b , Fiehler, J.a
Evidence of rapid ongoing brain development beyond 2 years of age detected by fiber tracking
(2008) American Journal of Neuroradiology, 29 (7), pp. 1261-1265. Cited 4 times.
a Department of Neuroradiology, University Medical Center Hamburg-Eppendorf, University of Hamburg, Hamburg, Germany
b Institute of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Hannover, Germany
c Institute of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Carl-Neuberg-Str 1, 30625 Hannover, Germany
Abstract
BACKGROUND AND PURPOSE: Development of callosal fibers is important for psychomotor and cognitive functions. We hypothesized that brain maturation changes are detectable beyond 2 years of age by using diffusion tensor imaging (DTI) of the corpus callosum (CC). MATERIALS AND METHODS: T2 and fractional anisotropy (FA) maps of the brain of 55 healthy subjects between 0.2 and 39 years of age were obtained. Quantitative T2 and FA values were measured at the genu and splenium of the CC (gCC and sCC). Fiber tracking, volumetric determination, and the fiber density calculations of the CC were related to age. A paired t test was used for significant differences between the values at the gCC and sCC. RESULTS: T2 relaxation times at gCC and sCC decrease fast in the first months of life and very little after 2 years of age. The FAgCC increases until 5 years of age and remains nearly constant thereafter; it showed a significant increase from 0 to 2 years versus 2-5 years, whereas there was no difference in the other age groups. FAsCC values showed no significant changes after 2 years of age. The fiber density of the CC shows a tendency of inverse age dependence from childhood to adulthood. CONCLUSION: Rapid ongoing changes in brain maturation (increase in FAgCC) are detectable until 5 years of age. DTI reveals more information about brain maturation than T2 relaxometry.
Document Type: Article
Source: Scopus
Liu, J.a , Gao, W.b , Huang, S.a , Nowinski, W.L.a
A model-based, semi-global segmentation approach for automatic 3-D point landmark localization in neuroimages
(2008) IEEE Transactions on Medical Imaging, 27 (8), art. no. 4384325, pp. 1034-1044.
a Biomedical Imaging Laboratory, Agency for Science, Technology and Research, 138671 Singapore, Singapore
b Bio-X Center, Harbin Institute of Technology, Harbin 150001, China
Abstract
The existing differential approaches for localization of 3-D anatomic point landmarks in 3-D images are sensitive to noise and usually extract numerous spurious landmarks. The parametric model-based approaches are not practically usable for localization of landmarks that can not be modeled by simple parametric forms. Some dedicated methods using anatomic knowledge to identify particular landmarks are not general enough to cope with other landmarks. In this paper, we propose a model-based, semi-global segmentation approach to automatically localize 3-D point landmarks in neuroimages. To localize a landmark, the semiglobal segmentation (meaning the segmentation of a part of the studied structure in a certain neighborhood of the landmark) is first achieved by an active surface model, and then the landmark is localized by analyzing the segmented part only. The joint use of global model-to-image registration, semi-global structure registration, active surface-based segmentation, and point-anchored surface registration makes our method robust to noise and shape variation. To evaluate the method, we apply it to the localization of ventricular landmarks including curvature extrema, centerline intersections, and terminal points. Experiments with 48 clinical and 18 simulated magnetic resonance (MR) volumetric images show that the proposed approach is able to localize these landmarks with an average accuracy of 1 mm (i.e., at the level of image resolution). We also illustrate the use of the proposed approach to cortical landmark identification and discuss its potential applications ranging from computer-aided radiology and surgery to atlas registration with scans. © 2008 IEEE.
Author Keywords
Brain atlas; Centerline; Cerebral ventricles; Curvature; Deformable model; Point-anchored surface registration; Semiglobal segmentation; Three-dimensional anatomic landmark
Document Type: Article
Source: Scopus
Towle, V.L.a b c d h , Yoon, H.-A.a , Castelle, M.a , Edgar, J.C.e f , Biassou, N.M.g , Frim, D.M.b , Spire, J.-P.a b , Kohrman, M.H.c
ECoG gamma activity during a language task: Differentiating expressive and receptive speech areas
(2008) Brain, 131 (8), pp. 2013-2027. Cited 2 times.
a Department of Neurology, University of Chicago, Chicago, IL 60637, United States
b Department of Surgery, University of Chicago, Chicago, IL 60637, United States
c Department of Pediatrics, University of Chicago, Chicago, IL 60637, United States
d Department of Psychiatry, University of Chicago, Chicago, IL 60637, United States
e Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, United States
f Center for Functional Brain Imaging, New Mexico VA Healthcare System, Albuquerque, NM, United States
g Division of Neuroradiology, Department of Imaging Sciences, National Institutes of Health, Bethesda, MD 20892, United States
h Department of Neurology, MC-2030, University of Chicago, 5841 S. Maryland Avenue, Chicago, IL 60637, United States
Abstract
Electrocorticographic (ECoG) spectral patterns obtained during language tasks from 12 epilepsy patients (age: 12-44 years) were analysed in order to identify and characterize cortical language areas. ECoG from 63 subdural electrodes (500 Hz/channel) chronically implanted over frontal, parietal and temporal lobes were examined. Two language tasks were performed. During the first language task, patients listened to a series of 50 words preceded by warning tones, and were asked to repeat each word. During a second memory task, subjects heard the 50 words from the first task randomly mixed with 50 new words and were asked to repeat the word only if it was a new word. Increases in ECoG gamma power (70-100 Hz) were observed in response to hearing tones (primary auditory cortex), hearing words (posterior temporal and parietal cortex) and repeating words (lateral frontal and anterior parietal cortex). These findings were compared to direct electrical stimulation and separate analysis of ECoG gamma changes during spontaneous inter-personal conversations. The results indicate that high-frequency ECoG reliably differentiates cortical areas associated with receptive and expressive speech processes for individual patients. Compared to listening to words, greater frontal lobe and decreased temporal lobe gamma activity was observed while speaking. The data support the concept of distributed functionally specific language modules interacting to serve receptive and expressive speech, with frontal lobe 'corollary discharges' suppressing low-level receptive cortical language areas in the temporal lobe during speaking. © The Author (2008). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved.
Author Keywords
Cortical mapping; Direct cortical stimulation; ECoG power; Electrocorticography; Epilepsy surgery; Functional mapping; Language mapping
Document Type: Article
Source: Scopus
Ziegler, A.a , Faber, C.b c , Mueller, S.d , Bartolomaeus, T.a
Systematic comparison and reconstruction of sea urchin (Echinoidea) internal anatomy: A novel approach using magnetic resonance imaging
(2008) BMC Biology, 6, art. no. 33, . Cited 3 times.
a Institut für Biologie, Freie Universität Berlin, Königin-Luise-Straße, 14195 Berlin, Germany
b Experimentelle Physik 5, Universität Würzburg, Am Hubland, 97074 Würzburg, Germany
c Institut für Klinische Radiologie, Universitätsklinikum Münster, Waldeyerstraße, 48149 Münster, Germany
d Berlin NeuroImaging Center, Charité-Universitätsmedizin Berlin, Charitéplatz, 10117 Berlin, Germany
Abstract
Background: Traditional comparative morphological analyses and subsequent three-dimensional reconstructions suffer from a number of drawbacks. This is particularly evident in the case of soft tissue studies that are technically demanding, time-consuming, and often prone to produce artefacts. These problems can partly be overcome by employing non-invasive, destruction-free imaging techniques, in particular micro-computed tomography or magnetic resonance imaging. Results: Here,we employed high-field magnetic resonance imaging techniques to gather numerous data from members of a major marine invertebrate taxon, the sea urchins (Echinoidea). For this model study, 13 of the 14 currently recognized high-ranking subtaxa (orders) of this group of animals were analyzed. Based on the acquired datasets, interactive three-dimensional models were assembled. Our analyses reveal that selected soft tissue characters can even be used for phylogenetic inferences in sea urchins, as exemplified by differences in the size and shape of the gastric caecum found in the Irregularia. Conclusion: The main focus of our investigation was to explore the possibility to systematically visualize the internal anatomy of echinoids obtained from various museum collections. We show that, in contrast to classical preparative procedures, magnetic resonance imaging can give rapid, destruction-free access to morphological data from numerous specimens, thus extending the range of techniques available for comparative studies of invertebrate morphology. © 2008 Ziegler et al; licensee BioMed Central Ltd.
Document Type: Article
Source: Scopus
El Ganaoui, O.a b c , Morandi, X.a b c d , Duchesne, S.b e , Jannin, P.a b c
Preoperative brain shift: Study of three surgical cases
(2008) Progress in Biomedical Optics and Imaging - Proceedings of SPIE, 6918, art. no. 691818, .
a INRIA, VisAGeS Project-Team, F-35042 Rennes, France
b INSERM, U746, F-35043 Rennes, France
c University of Rennes I, CNRS, UMR 6074, IRISA, F-35042 Rennes, France
d Hospital of Rennes, Department of Neurosurgery, F-35033 Rennes, France
e Centre de Recherche de l'Université Laval - Robert Giffard, 2601 De La Canardière Beauport QC G1J 2G3
Abstract
In successful brain tumor surgery, the neurosurgeon's objectives are threefold: (1) reach the target, (2) remove it and (3) preserve eloquent tissue surrounding it. Surgical Planning (SP) consists in identifying optimal access route(s) to the target based on anatomical references and constrained by functional areas, Preoperative images are essential input in Multi-modal Image Guided NeuroSurgery systems (MIGNS) and update of these images, with precision and accuracy, is crucial to approach the anatomical reality in the Operating Room (OR). Intraoperative brain deformation has been previously identified by many research groups and related update of preoperative images has also been studied. We present a study of three surgical cases with tumors accompanied with edema and where corticosteroids were administered and monitored during a preoperative stage [t0, t1 = t0 + 10 days]. In each case we observed a significant change in the Region Of Interest (ROI) and in anatomical references around it. This preoperative brain shift could induce error for localization during intervention (time ts) if the SP is based on the t0 preoperative images. We computed volume variation, distance maps based on closest point (CP) for different components of the ROI, and displacement of center of mass (CM) of the ROI, The matching between sets of homologous landmarks from t0 to t1 was performed by an expert. The estimation of the landmarks displacement showed significant deformations around the ROI (landmarks shifted with mean of 3.90 ± 0.92 mm and maximum of 5.45 mm for one case resection). The CM of the ROI moved about 6.92 mm for one biopsy. Accordingly, there was a sizable difference between SP based at t0 vs SP based at t1, up to 7.95 mm for localization of reference access in one resection case. When compared to the typical MIGNS system accuracy (2 mm), it is recommended that preoperative images be updated within the interval time [t1,ts[ in order to minimize the error correspondence between the anatomical reality and the preoperative data. This should help maximize the accuracy of registration between the preoperative images and the patient in the OR.
Author Keywords
Brain shift; MIGNS; Neurological procedures; Surgical workflow
Document Type: Conference Paper
Source: Scopus
Salama, P.
A least squares approach to estimating the probability distribution of unobserved data in multi-photon microscopy
(2008) Proceedings of SPIE - The International Society for Optical Engineering, 6814, art. no. 68140U, .
Department of Electrical and Computer Engineering, Indiana University, 723 West Michigan Street, SL160, Indianapolis, IN 46202, United States
Abstract
Multi-photon microscopy has provided biologists with unprecedented opportunities for high resolution imaging deep into tissues. Unfortunately deep tissue multi-photon microscopy images are in general noisy since they are acquired at low photon counts. To aid in the analysis and segmentation of such images it is sometimes necessary to initially enhance the acquired images. One way to enhance an image is to find the maximum a posteriori (MAP) estimate of each pixel comprising an image, which is achieved by finding a constrained least squares estimate of the unknown distribution. In arriving at the distribution it is assumed that the noise is Poisson distributed, the true but unknown pixel values assume a probability mass function over a finite set of non-negative values, and since the observed data also assumes finite values because of low photon counts, the sum of the probabilities of the observed pixel values (obtained from the histogram of the acquired pixel values) is less than one. Experimental results demonstrate that it is possible to closely estimate the unknown probability mass function with these assumptions. © 2008 SPIE-IS&T.
Author Keywords
Deblurring; Deconvolution; Image enhancement; Image segmentation; Least squares; MAP estimate; Multi-photon microscopy; Noise; Poisson distribution
Document Type: Conference Paper
Source: Scopus
Neu, S.C., Toga, A.W.
Automatic localization of anatomical point landmarks for brain image processing algorithms
(2008) Neuroinformatics, 6 (2), pp. 135-148. Cited 1 time.
Department of Neurology, UCLA Laboratory of Neuro Imaging, David Geffen School of Medicine, 635 Charles Young Drive South, Los Angeles, CA 90095-7334, United States
Abstract
Many brain image processing algorithms require one or more well-chosen seed points because they need to be initialized close to an optimal solution. Anatomical point landmarks are useful for constructing initial conditions for these algorithms because they tend to be highly-visible and predictably-located points in brain image scans. We introduce an empirical training procedure that locates user-selected anatomical point landmarks within well-defined precisions using image data with different resolutions and MRI weightings. Our approach makes no assumptions on the structural or intensity characteristics of the images and produces results that have no tunable run-time parameters. We demonstrate the procedure using a Java GUI application (LONI ICE) to determine the MRI weighting of brain scans and to locate features in T1-weighted and T2-weighted scans. © 2008 Humana Press.
Author Keywords
Anatomical point landmark; Automation; Least-squares; Multi-resolution; Neural network; Seed points; Singular value decomposition
Document Type: Article
Source: Scopus
Yushkevich, P.A.a , Zhang, H.a , Simon, T.J.b , Gee, J.C.a
Structure-specific statistical mapping of white matter tracts
(2008) NeuroImage, 41 (2), pp. 448-461. Cited 8 times.
a Penn Image Computing and Science Laboratory (PICSL), Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States
b Department of Psychiatry and Behavioral Sciences, M.I.N.D. Institute, University of California, Davis, CA, United States
Abstract
We present a new model-based framework for the statistical analysis of diffusion imaging data associated with specific white matter tracts. The framework takes advantage of the fact that several of the major white matter tracts are thin sheet-like structures that can be effectively modeled by medial representations. The approach involves segmenting major tracts and fitting them with deformable geometric medial models. The medial representation makes it possible to average and combine tensor-based features along directions locally perpendicular to the tracts, thus reducing data dimensionality and accounting for errors in normalization. The framework enables the analysis of individual white matter structures, and provides a range of possibilities for computing statistics and visualizing differences between cohorts. The framework is demonstrated in a study of white matter differences in pediatric chromosome 22q11.2 deletion syndrome. © 2008 Elsevier Inc. All rights reserved.
Author Keywords
Deformable models; Diffusion tensor imaging; DS22q11.2; Medial representation; Skeletons; Statistical mapping; White matter
Document Type: Article
Source: Scopus
Styner, M.a b , Knickmeyer, R.a , Coe, C.c , Short, S.J.c , Gilmore, J.a
Automatic regional analysis of DTI properties in the developmental macaque brain
(2008) Progress in Biomedical Optics and Imaging - Proceedings of SPIE, 6914, art. no. 69142K, .
a Department of Psychiatry, University of North Carolina, Chapel Hill, NC, United States
b Department of Computer Science, University of North Carolina, Chapel Hill, NC, United States
c Department of Psychology, University of Wisconsin, Madison, WI, United States
Abstract
Many neuroimaging studies are applied to monkeys as pathologies and environmental exposures can be studied in well-controlled settings and environment. In this work, we present a framework for the use of an atlas based, fully automatic segmentation of brain tissues, lobar parcellations, subcortical structures and the regional extraction of Diffusion Tensor Imaging (DTI) properties. We first built a structural atlas from training images by iterative, joint deformable registration into an unbiased average image. On this atlas, probabilistic tissue maps, a lobar parcellation and subcortical structures were determined. This information is applied to each subjects structural image via affine, followed by deformable registration. The affinely transformed atlas is employed for a joint T1 and T2 based tissue classification. The deformed parcellation regions mask the tissue segmentations to define the parcellation for white and gray matter separately. Each subjects structural image is then non-rigidly matched with its DTI image by normalized mutual information, b-spline based registration. The DTI property histograms were then computed using the probabilistic white matter information for each lobar parcellation. We successfully built using a developmental training datasets of 18 ged 16-34 months. Our framework was successfully applied to over 50 additional subjects in the age range of 9 70 months. The probabilistically weighted FA average in the corpus callosum region showed the largest increase over time in the observed age range. Most cortical regions show modest FA increase, whereas the cerebellums FA values remained stable. The individual methods used in this segmentation framework have been applied before, but their combination is novel, as is their application to macaque MRI data. Furthermore, this is the first study to date looking at the DTI properties of the developing macaque brain.
Document Type: Conference Paper
Source: Scopus
Solberg, O.V.a b , Tangen, G.-A.a , Lindseth, F.a , Sandnes, T.a , Enquobahrie, A.A.c , Ibáñez, L.c , Cheng, P.d , Gobbi, D.e f , Cleary, K.d
Integration of a real-time video grabber component with the open source image-guided surgery toolkit IGSTK
(2008) Progress in Biomedical Optics and Imaging - Proceedings of SPIE, 6919, art. no. 69190Z, .
a SINTEF Health Research, Medical Technology and National Center for 3D Ultrasound in Surgery, Trondheim, Norway
b Norwegian University of Science and Technology (NTNU), Faculty of Medicine, Department of Circulation and Medical Imaging, Trondheim, Norway
c Kitware Inc., New York, NY, United States
d Imaging Science and Information Systems (ISIS) Center, Department of Radiology, Washington, DC, United States
e Atamai Inc., London, ON, Canada
f School of Computing, Queen's University, Kingston, ON, Canada
Abstract
The image-guided surgery toolkit (IGSTK) is an open source C++ library that provides the basic components required for developing image-guided surgery applications. While the initial version of the toolkit has been released, some additional functionalities are required for certain applications. With increasing demand for real-time intraoperative image data in image-guided surgery systems, we are adding a video grabber component to IGSTK to access intraoperative imaging data such as video streams. Intraoperative data could be acquired from real-time imaging modalities such as ultrasound or endoscopic cameras. The acquired image could be displayed as a single slice in a 2D window or integrated in a 3D scene. For accurate display of the intraoperative image relative to the patient's preoperative image, proper interaction and synchronization with IGSTK's tracker and other components is necessary. Several issues must be considered during the design phase: 1) Functions of the video grabber component 2) Interaction of the video grabber component with existing and future IGSTK components; and 3) Layout of the state machine in the video grabber component. This paper describes the video grabber component design and presents example applications using the video grabber component.
Author Keywords
Image-guided surgery; Intraoperative imaging; Open source software; Ultrasound; Video import
Document Type: Conference Paper
Source: Scopus
Rexilius, J., Peitgen, H.-O.
Rapid prototyping of clinical software assistants
(2008) Progress in Biomedical Optics and Imaging - Proceedings of SPIE, 6919, art. no. 69190S, .
MeVis Research, Universitaetsallee, Bremen, Germany
Abstract
Computer assistance in image-based diagnosis and therapy are continuously growing fields that have gained importance in several medical disciplines. Today, various free and commercial tools are available. However, only few are routinely applied in clinical practice. Especially tools that provide a flexible support of the whole design process from development and evaluation to the actual deployment in a clinical environment are missing. In this work, we introduce a categorization of the design process into different types and fields of application. To this end, we propose a novel framework that allows the development of software assistants that can be integrated into the design process of new algorithms and systems. We focus on the specific features of software prototypes that are valuable for engineers and clinicians, rather than on product development. An important aspect in this work is the categorization of the software design process into different components. Furthermore, we examine the interaction between these categories based on a new knowledge flow model. Finally, an encapsulation of these tasks within an application framework is proposed. We discuss general requirements and present a layered architecture. Several components for data- and workflow-management provide a generic functionality that can be customized on the developer and the user level. A flexible handling of is offered through the use of a visual programming and rapid prototyping platform. Currently, the framework is used in 15 software prototypes and as a basis of commercial products. More than 90 clinical partners all over the world work with these tools.
Author Keywords
Application framework; Clinical software assistants; Rapid prototyping
Document Type: Conference Paper
Source: Scopus
Tran, P.T.a b c , Fan, A.C.b c , Bendapudi, P.K.b c , Koh, S.b c , Komatsubara, K.b c , Chen, J.b c , Horng, G.b c , Bellovin, D.I.b c , Giuriato, S.d e , Wang, C.S.b c , Whitsett, J.A.f , Felsher, D.W.b c
Combined inactivation of MYC and K-ras oncogenes reverses tumorigenesis in lung adenocarcinomas and lymphomas
(2008) PLoS ONE, 3 (5), art. no. e2125, . Cited 6 times.
a Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA, United States
b Division of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA, United States
c Division of Oncology, Department of Pathology, Stanford University School of Medicine, Stanford, CA, United States
d Institut National de la Santé et de la Recherche Médicale (INSERM), U563, Centre de Physiopathologie Toulouse Purpuan, Toulouse, France
e Université Paul-Sabatier, Toulouse, France
f Division of Pulmonary Biology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, OH, United States
Abstract
Background: Conditional transgenic models have established that tumors require sustained oncogene activation for tumor maintenance, exhibiting the phenomenon known as "oncogene-addiction." However, most cancers are caused by multiple genetic events making it difficult to determine which oncogenes or combination of oncogenes will be the most effective targets for their treatment. Methodology/Principal Findings: To examine how the MYC and K-rasG12D oncogenes cooperate for the initiation and maintenance of tumorigeneses, we generated double conditional transgenic tumor models of lung adenocarcinoma and lymphoma. The ability of MYC and K-rasG12D to cooperate for tumorigenesis and the ability of the inactivation of these oncogenes to result in tumour regression depended upon the specific tissue content. MYC-, K-rasG12D- or MYC/K-rasG12D- induced lymphomas exhibited sustained regression upon the inactivation of either or both oncogenes. However, in marked contrast MYC-induced lung tumors failed to regress completely upon oncogene inactivation; whereas K-rasG12D- induced lung tumors regressed completely. Importantly, the combined inactivation of both MYC and K-rasG12D resulted more frequently in complete lung tumor regression. To account for the different roles of MYC and K-rasG1D in maintenance of lung tumors, we found that the down-stream mediates of K-ras G12D signaling, Stat3 and Stat5, are dephosphorylated following conditional K-rasG12D but not MYC inactivation. In contrast, Stat3 becomes dephosphorylated in lymphoma cells upon inactivation of MYC and/or K-rasG12D. Interestingly, MYC-induced lung tumors that failed to regress upon MYC inactivation were found to have persistent Stat3 and Stat5 phosphorylation. Conclusions/Significance: Taken together, our findings point to the importance of the K-Ras and associated down-stream Stat effector pathways in the initiation and maintenance of lymphomas and lung tumors. We suggest that combined targeting of oncogenic pathways is more likely to be effective in the treatment of lung cancers and lymphomas. © 2008 Tran et al.
Document Type: Article
Source: Scopus
Apostolova, L.G.a b , Thompson, P.M.a b
Mapping progressive brain structural changes in early Alzheimer's disease and mild cognitive impairment
(2008) Neuropsychologia, 46 (6), pp. 1597-1612. Cited 3 times.
a Department of Neurology, David Geffen School of Medicine, UCLA, CA, United States
b Laboratory of Neuro Imaging, David Geffen School of Medicine, UCLA, CA, United States
Abstract
Alzheimer's disease (AD), the most common neurodegenerative disorder of the elderly, ranks third in health care cost after heart disease and cancer. Given the disproportionate aging of the population in all developed countries, the socio-economic impact of AD will continue to rise. Mild cognitive impairment (MCI), a transitional state between normal aging and dementia, carries a four- to sixfold increased risk of future diagnosis of dementia. As complete drug-induced reversal of AD symptoms seems unlikely, researchers are now focusing on the earliest stages of AD where a therapeutic intervention is likely to realize the greatest impact. Recently neuroimaging has received significant scientific consideration as a promising in vivo disease-tracking modality that can also provide potential surrogate biomarkers for therapeutic trials. While several volumetric techniques laid the foundation of the neuroimaging research in AD and MCI, more precise computational anatomy techniques have recently become available. This new technology detects and visualizes discrete changes in cortical and hippocampal integrity and tracks the spread of AD pathology throughout the living brain. Related methods can visualize regionally specific correlations between brain atrophy and important proxy measures of disease such as neuropsychological tests, age of onset or factors that may influence disease progression. We describe extensively validated cortical and hippocampal mapping techniques that are sensitive to clinically relevant changes even in the single individual, and can identify group differences in epidemiological studies or clinical treatment trials. We give an overview of some recent neuroimaging advances in AD and MCI and discuss strengths and weaknesses of the various analytic approaches.
Author Keywords
Alzheimer's disease; Brain mapping; Cortical atrophy; Hippocampal atrophy; Mild cognitive impairment (MCI); MRI; Neuroimaging; Ventricular expansion
Document Type: Article
Source: Scopus
Chou, Y.-Y.a , Leporé, N.a , de Zubicaray, G.I.b , Carmichael, O.T.c , Becker, J.T.d , Toga, A.W.a , Thompson, P.M.a
Automated ventricular mapping with multi-atlas fluid image alignment reveals genetic effects in Alzheimer's disease
(2008) NeuroImage, 40 (2), pp. 615-630. Cited 9 times.
a Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, 635 Charles E. Young Dr. South, Suite 225E, Los Angeles, CA, United States
b Centre for Magnetic Resonance, University of Queensland, Brisbane, Australia
c Departments of Neurology and Computer Science, University of California, Davis, CA, United States
d Department of Neurology, Alzheimer's Disease Research Center, University of Pittsburgh Medical Center, Pittsburgh, PA, United States
Abstract
We developed and validated a new method to create automated 3D parametric surface models of the lateral ventricles in brain MRI scans, providing an efficient approach to monitor degenerative disease in clinical studies and drug trials. First, we used a set of parameterized surfaces to represent the ventricles in four subjects' manually labeled brain MRI scans (atlases). We fluidly registered each atlas and mesh model to MRIs from 17 Alzheimer's disease (AD) patients and 13 age- and gender-matched healthy elderly control subjects, and 18 asymptomatic ApoE4-carriers and 18 age- and gender-matched non-carriers. We examined genotyped healthy subjects with the goal of detecting subtle effects of a gene that confers heightened risk for Alzheimer's disease. We averaged the meshes extracted for each 3D MR data set, and combined the automated segmentations with a radial mapping approach to localize ventricular shape differences in patients. Validation experiments comparing automated and expert manual segmentations showed that (1) the Hausdorff labeling error rapidly decreased, and (2) the power to detect disease- and gene-related alterations improved, as the number of atlases, N, was increased from 1 to 9. In surface-based statistical maps, we detected more widespread and intense anatomical deficits as we increased the number of atlases. We formulated a statistical stopping criterion to determine the optimal number of atlases to use. Healthy ApoE4-carriers and those with AD showed local ventricular abnormalities. This high-throughput method for morphometric studies further motivates the combination of genetic and neuroimaging strategies in predicting AD progression and treatment response. © 2007 Elsevier Inc. All rights reserved.
Document Type: Article
Source: Scopus
Langø, T.a b , Tangen, G.A.a b , Mårvik, R.b c d e , Ystgaard, B.b f , Yavuz, Y.d , Kaspersen, J.H.a b , Solberg, O.V.a b e , Hernes, T.A.N.a b e
Navigation in laparoscopy - Prototype research platform for improved image-guided surgery
(2008) Minimally Invasive Therapy and Allied Technologies, 17 (1), pp. 17-33. Cited 2 times.
a SINTEF Health Research, Dept. Medical Technology, Trondheim, Norway
b National Center for 3D Ultrasound in Surgery, Trondheim, Norway
d National Center for Advanced Laparoscopic Surgery, St. Olavs Hospital, Trondheim, Norway
e Norwegian University of Science and Technology (NTNU), Trondheim, Norway
f Department of Surgery, St. Olavs Hospital, Trondheim, Norway
Abstract
The manipulation of the surgical field in laparoscopic surgery, through small incisions with rigid instruments, reduces free sight, dexterity, and tactile feedback. To help overcome some of these drawbacks, we present a prototype research and development platform, CustusX, for navigation in minimally invasive therapy. The system can also be used for planning and follow-up studies. With this platform we can import and display a range of medical images, also real-time data such as ultrasound and X-ray, during surgery. Tracked surgical tools, such as pointers, video laparoscopes, graspers, and various probes, allow surgeons to interactively control the display of medical images during the procedure. This paper introduces navigation technologies and methods for laparoscopic therapy, and presents our software and hardware research platform. Furthermore, we illustrate the use of the system with examples from two pilots performed during laparoscopic therapy. We also present new developments that are currently being integrated into the system for future use in the operating room. Our initial results from pilot studies using this technology with preoperative images and guidance in the retroperitoneum during laparoscopy are promising. Finally, we shortly describe an ongoing multicenter study using this surgical navigation system platform.
Author Keywords
Image-guided surgery; Laparoscopy; Minimally invasive surgery; Surgical navigation; Ultrasound
Document Type: Article
Source: Scopus
Kim, J.a , Avants, B.b , Patel, S.a , Whyte, J.a c , Coslett, B.H.d , Pluta, J.e , Detre, J.A.b d e , Gee, J.C.b
Structural consequences of diffuse traumatic brain injury: A large deformation tensor-based morphometry study
(2008) NeuroImage, 39 (3), pp. 1014-1026. Cited 7 times.
a Moss Rehabilitation Research Institute, Albert Einstein Healthcare Network, Philadelphia, PA, United States
b Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States
c Department of Rehabilitation Medicine, Thomas Jefferson University, Philadelphia, PA, United States
d Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
e Center for Functional Neuroimaging, University of Pennsylvania, Philadelphia, PA, United States
Abstract
Traumatic brain injury (TBI) is one of the most common causes of long-term disability. Despite the importance of identifying neuropathology in individuals with chronic TBI, methodological challenges posed at the stage of inter-subject image registration have hampered previous voxel-based MRI studies from providing a clear pattern of structural atrophy after TBI. We used a novel symmetric diffeomorphic image normalization method to conduct a tensor-based morphometry (TBM) study of TBI. The key advantage of this method is that it simultaneously estimates an optimal template brain and topology preserving deformations between this template and individual subject brains. Detailed patterns of atrophies are then revealed by statistically contrasting control and subject deformations to the template space. Participants were 29 survivors of TBI and 20 control subjects who were matched in terms of age, gender, education, and ethnicity. Localized volume losses were found most prominently in white matter regions and the subcortical nuclei including the thalamus, the midbrain, the corpus callosum, the mid- and posterior cingulate cortices, and the caudate. Significant voxel-wise volume loss clusters were also detected in the cerebellum and the frontal/temporal neocortices. Volume enlargements were identified largely in ventricular regions. A similar pattern of results was observed in a subgroup analysis where we restricted our analysis to the 17 TBI participants who had no macroscopic focal lesions (total lesion volume > 1.5 cm3). The current study confirms, extends, and partly challenges previous structural MRI studies in chronic TBI. By demonstrating that a large deformation image registration technique can be successfully combined with TBM to identify TBI-induced diffuse structural changes with greater precision, our approach is expected to increase the sensitivity of future studies examining brain-behavior relationships in the TBI population. © 2007 Elsevier Inc. All rights reserved.
Author Keywords
Atrophy; Diffeomorphic; Magnetic resonance imaging; Tensor-based morphometry; Traumatic brain injury
Document Type: Article
Source: Scopus
Moussa, C.E.-H.a , Rusnak, M.a , Hailu, A.b , Sidhu, A.a , Fricke, S.T.b
Alterations of striatal glutamate transmission in rotenone-treated mice: MRI/MRS in vivo studies
(2008) Experimental Neurology, 209 (1), pp. 224-233. Cited 2 times.
a Laboratory of Molecular Neurochemistry, Department of Biochemistry, Molecular and Cell Biology, Georgetown University Medical Center, New Research Building, 3970 Reservoir Rd, NW Washington, DC 20007, United States
b Neuroscience, Georgetown University Medical Center, Washington, DC 20007, United States
Abstract
Animal models treated with agricultural chemicals, such as rotenone, reproduce several degenerative features of human central nervous system (CNS) diseases. Glutamate is the most abundant excitatory amino acid transmitter in the mammalian central nervous system and its transmission is implicated in a variety of brain functions including mental behavior and memory. Dysfunction of glutamate neurotransmission in the CNS has been associated with a number of human neurodegenerative diseases, either as a primary or as a secondary factor in the excitotoxic events leading to neuronal death. Since many human CNS disorders do not arise spontaneously in animals, characteristic functional changes have to be mimicked by toxic agents. Candidate environmental toxins bearing any direct or indirect effects on the pathogenesis of human disease are particularly useful. The present longitudinal Magnetic Resonance Imaging (MRI) studies show, for the first time, significant variations in the properties of brain ventricles in a rotenone-treated (2 mg/kg) mouse model over a period of 4 weeks following 3 days of rotenone treatment. Histopathological analysis reveals death of stria terminalis neurons following this short period of rotenone treatment. Furthermore, in vivo voxel localized 1H MR spectroscopy also shows for the first time significant bio-energetic and metabolic changes as well as temporal alterations in the levels of glutamate in the degenerating striatal region. These studies provide novel insights on the effects of environmental toxins on glutamate and other amino acid neurotransmitters in human neurodegenerative diseases. © 2007 Elsevier Inc. All rights reserved.
Author Keywords
1H MRS; Glutamate; In vivo; MRI; Neurodegeneration; Rotenone; Striatum
Document Type: Article
Source: Scopus
McClure, R.K.a , Carew, K.a , Greeter, S.a , Maushauer, E.a , Steen, G.a , Weinberger, D.R.b
Absence of regional brain volume change in schizophrenia associated with short-term atypical antipsychotic treatment
(2008) Schizophrenia Research, 98 (1-3), pp. 29-39. Cited 5 times.
a University of North Carolina at Chapel Hill, Department of Psychiatry, Chapel Hill, NC, United States
b Clinical Brain Disorders Branch, NIMH, Bethesda, MD, United States
Abstract
The first aim of this pilot study was to determine if longitudinal change in caudate volume could be detected in chronic schizophrenic patients after 12 weeks of atypical antipsychotic treatment. A sub-aim of the first aim was to determine if similar results could be obtained from an operator-assisted segmentation tool for volumetric imaging (ITK-SNAP) and voxel-based morphometry (VBM) methods in the caudate. The second aim was to determine if frontal and temporal lobe grey matter, white matter, ventricular and sulcal cerebrospinal fluid volume change could be detected after 12 weeks of atypical antipsychotic treatment with VBM. Ten chronic schizophrenic inpatients, with illness duration averaging 10.6 years, underwent two MRI scans. The first scan was obtained after a mean of 39.4 days of antipsychotic withdrawal. The second MRI was obtained following twelve weeks of atypical antipsychotic treatment. Caudate volume change was first measured with ITK-SNAP. Then the location of grey matter volume change in the caudate was identified with VBM. Finally, the location of frontal and temporal lobe grey matter, white matter, ventricular and sulcal cerebrospinal fluid volume changes were identified with VBM. No longitudinal change in caudate volume or grey matter volume was observed after brief periods of atypical antipsychotic treatment. ITK-SNAP and VBM methods showed very similar results in the caudate. No statistically significant change was identified in the volume of frontal or temporal lobe grey matter, white matter, and lateral, third, or fourth ventricular cerebrospinal fluid. Although the results do not directly show that brief periods of atypical antipsychotic treatment are associated with basal ganglia and cortical volume change, there is much evidence to suggest that such an association exists. © 2007.
Author Keywords
Atypical antipsychotic; Caudate; Chronic schizophrenia; First episode; ITK-SNAP; Treatment naïve; VBM; Voxel-based morphometry
Document Type: Article
Source: Scopus
Aliroteh, M., McInerney, T.
SketchSurfaces: Sketch-line initialized deformable surfaces for efficient and controllable interactive 3D medical image segmentation
(2007) Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4841 LNCS (PART 1), pp. 542-553.
Depts. of Computer Science and Electrical Engineering, Ryerson University, Toronto, Ont. M5B 2K3, Canada
Abstract
We present an intuitive, fast and accurate interactive segmentation method for extracting and visualizing a large range of objects from 3D medical images. Our method combines a general deformable subdivision-surface model with a novel sketch-line user initialization process. The model is simply and precisely initialized with a few quick sketch lines drawn across the width of the target object on several key slices of the volume image. The smooth surface constructed using these lines is extremely close to the shape of the object boundary, making the model's task of snapping to this boundary much simpler and hence more likely to succeed in noisy images with minimal user editing. Our subdivision surface model provides a foundation for precise user steering/editing capabilities and simple, intuitive user interactions are seamlessly integrated with advanced visualization capabilities. We use our model to segment objects from several 3D medical images to demonstrate its effectiveness. © Springer-Verlag Berlin Heidelberg 2007.
Document Type: Conference Paper
Source: Scopus
He, Q.a , Duan, Y.a , Miles, J.b , Takahashi, N.b
A context-sensitive active contour for 2D corpus callosum segmentation
(2007) International Journal of Biomedical Imaging, 2007, art. no. 24826, . Cited 2 times.
a Department of Computer Science, College of Engineering, University of Missouri-Columbia, Columbia, MO 65211, United States
b Thompson Center for Autism, University of Missouri-Columbia, Columbia, MO 65211, United States
Abstract
We propose a new context-sensitive active contour for 2D corpus callosum segmentation. After a seed contour consisting of interconnected parts is being initialized by the user, each part will start to deform according to its own motion law derived from high-level prior knowledge, and is constantly aware of its own orientation and destination during the deformation process. Experimental results demonstrate the accuracy and robustness of our algorithm.
Document Type: Article
Source: Scopus
Pohl, K.M.a b , Kikinis, R.a , Wells, W.M.a b
Active mean fields: Solving the mean field approximation in the level set framework
(2007) Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4584 LNCS, pp. 26-37. Cited 1 time.
a Surgical Planning Laboratory, Harvard Medical School, Brigham and Women's Hospital, Boston, MA, United States
b Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, MA, United States
Abstract
We describe a new approach for estimating the posterior probability of tissue labels. Conventional likelihood models are combined with a curve length prior on boundaries, and an approximate posterior distribution on labels is sought via the Mean Field approach. Optimizing the resulting estimator by gradient descent leads to a level set style algorithm where the level set functions are the logarithm-of-odds encoding of the posterior label probabilities in an unconstrained linear vector space. Applications with more than two labels are easily accommodated. The label assignment is accomplished by the Maximum A Posteriori rule, so there are no problems of "overlap" or "vacuum". We test the method on synthetic images with additive noise. In addition, we segment a magnetic resonance scan into the major brain compartments and subcortical structures. © Springer-Verlag Berlin Heidelberg 2007.
Document Type: Conference Paper
Source: Scopus
Rizzi, S.H., Banerjee, P.P., Luciano, C.J.
Automating the extraction of 3D models from medical images for virtual reality and haptic simulations
(2007) Proceedings of the 3rd IEEE International Conference on Automation Science and Engineering, IEEE CASE 2007, art. no. 4341748, pp. 152-157.
Department of Mechanical and Industrial Engineering, University of Illinois, Chicago, IL 60607, United States
Abstract
The Sensimmer platform represents our ongoing research on simultaneous haptics and graphics rendering of 3D models. For simulation of medical and surgical procedures using Sensimmer, 3D models must be obtained from medical imaging data, such as Magnetic Resonance Imaging (MRI) or Computed Tomography (CT). Image segmentation techniques are used to determine the anatomies of interest from the images. 3D models are obtained from segmentation and their triangle reduction is required for graphics and haptics rendering. This paper focuses on creating an integrated interface between Sensimmer and medical imaging devices, using available software. Existing tools are evaluated, as well as aspects that require further development are identified. Solutions to overcome limitations and increase the degree of automation of the process are examined. © 2007 IEEE.
Document Type: Conference Paper
Source: Scopus
Mueller, D.a , Maeder, A.b , O'Shea, P.a
Tracking-based segmentation and volume rendering for assessing stenosis of coronary arteries in MS-CTA images
(2007) Proceedings of the 9th IASTED International Conference on Computer Graphics and Imaging, CGIM 2007, pp. 108-113.
a School of Engineering Systems, Queensland University of Technology, Brisbane, QLD, Australia
b e-Health Research Centre, CSIRO ICT Centre, Brisbane, QLD, Australia
Abstract
Multi-slice spiral computed tomography angiography (MSCTA) is emerging as a clinically robust modality for diagnosis and surgical planning for coronary heart disease. To enable these tasks the coronary arteries must be segmented and visualised. This paper proposes the use of an improved tracking-based algorithm for segmenting the coronary artery network. The segmentation results are coupled with direct volume rendering allowing for the 3-D visualisation of the degree of stenosis. We represent vessels using a generalised-cylinder model, which facilitates fast segmentation and the visualisation of vessel cross-sectional area. A number of synthetic and in vivo datasets are used to validate and demonstrate the approach.
Author Keywords
Imaging and image processing; Medical imaging; Vessel segmentation; Volume rendering
Document Type: Conference Paper
Source: Scopus
Liu, J., Huang, S., Aziz, A., Nowinski, W.L.
Three dimensional digital atlas of the orbit constructed from multi-modal radiological images
(2007) International Journal of Computer Assisted Radiology and Surgery, 1 (5), pp. 275-283. Cited 3 times.
Biomedical Imaging Lab, Agency for Science, Technology and Research, 30 Biopolis Street, Singapore 138671, Singapore
Abstract
The human orbit has numerous structures packed in a relatively small space, the study of which is essential and difficult due to complex three dimensional relationships. Available printed orbital atlases do not convey the three dimensional information and are not interactive. To overcome these limitations, we built a digital 3D orbital atlas presented in axial, coronal and sagittal planes, and as three dimensional geometric models of the muscles, bones, and eyeball. The bone models are from a CT scan, the muscle and optic nerve from a MR scan, and other components that cannot be distinguished radiologically are modeled as geometric primitives from anatomic literature. All multi-modal data including the models and images are registered into the same space to form a complete atlas. All structures in the atlas are labeled with their names. An atlas browser is developed for user-friendly manipulation and presentation of the atlas content. Each structure can be turned on or off, rotated, zoomed, or moved, either individually or in unison with other selected structures. Thus, the relationships between different structures can be studied in greater depth. The method developed to build the orbital atlas is general and can be used to create other atlases or to build patient specific geometric models. The orbital atlas may be used for studying the orbital anatomy, as a reference guide for practitioners, and as a base for simulation of orbital surgery. © CARS 2007.
Author Keywords
Active surface; Geometric modeling; Image registration; Livewire; Orbital atlas; Shape interpolation; Surgery simulation
Document Type: Article
Source: Scopus
Mani, M.a b , Chou, Y.-Y.a , Leporé, N.a , Lee, A.a , De Leeuw, J.b , McMahon, K.c , Wright, M.c , Toga, A.a , Thompson, P.M.a
Mapping genetic influences on brain shape using multi-atlas fluid image alignment
(2007) Proceedings of the Frontiers in the Convergence of Bioscience and Information Technologies, FBIT 2007, art. no. 4524153, pp. 482-489.
a Laboratory of NeuroImaging, University of California-Los Angeles, Los Angeles, United States
b Department of Statistics, University of California-Los Angeles, Los Angeles, United States
c Centre for Magnetic Resonance, University of Queensland, Brisbane, Australia
Abstract
In this pilot study, we developed a set of computer vision based surface segmentation and statistical shape analysis algorithms to study genetic influences on brain structure in a database of brain MRI scans of normal twins. A set of manually delineated 3D parametric surfaces, representing the lateral ventricles, was deformed, using a Navier-Stokes fluid image registration algorithm, onto all the images in the database. The geometric transformations thus obtained were used to propagate the segmentation labels to all the other images. 3D radial distance maps were derived to encode anatomical shape differences. The proportion of shape variance attributable to genetic factors, known as the heritability, was estimated from the shape models using a restricted maximum likelihood method to increase statistical power. Segmentation errors associated with projecting labels onto new images were greatly reduced through multiatlas averaging. The resulting algorithms provide a convenient and sensitive tool to recover and analyze small intrapair image differences, and will make it easier to detect genetic influences on brain structure. © 2007 IEEE.
Document Type: Conference Paper
Source: Scopus
Styner, M.a b , Smith, R.G.b , Graves, M.M.b , Mosconi, M.W.b , Peterson, S.b , White, S.b , Blocher, J.b , El-Sayed, M.c , Hazlett, H.C.b
Asymmetric bias in user guided segmentations of brain structures
(2007) Progress in Biomedical Optics and Imaging - Proceedings of SPIE, 6512 (PART 1), art. no. 65120K, .
a Department of Psychiatry, University of North Carolina, Chapel Hill, NC, United States
b Department of Computer Science, University of North Carolina, Chapel Hill, NC, United States
c Mansoura University, Mansoura, Egypt
Abstract
Brain morphometric studies often incorporate comparative asymmetry analyses of left and right hemispheric brain structures. In this work we show evidence that common methods of user guided structural segmentation exhibit strong left-right asymmetric biases and thus fundamentally influence any left-right asymmetry analyses. We studied several structural segmentation methods with varying degree of user interaction from pure manual outlining to nearly fully automatic procedures. The methods were applied to MR images and their corresponding left-right mirrored images from an adult and a pediatric study. Several expert raters performed the segmentations of all structures. The asymmetric segmentation bias is assessed by comparing the left-right volumetric asymmetry in the original and mirrored dataseis, as well as by testing each sides volumetric differences to a zero mean standard t-tests. The structural segmentations of caudate, putamen, globus pallidus, amygdala and hippocampus showed a highly significant asymmetric bias using methods with considerable manual outlining or landmark placement. Only the lateral ventricle segmentation revealed no asymmetric bias due to the high degree of automation and a high intensity contrast on its boundary. Our segmentation methods have been adapted in that they are applied to only one of the hemispheres in an image and its left-right mirrored image. Our work suggests that existing studies of hemispheric asymmetry without similar precautions should be interpreted in a new, skeptical light. Evidence of an asymmetric segmentation bias is novel and unknown to the imaging community. This result seems less surprising to the visual perception community and its likely cause is differences in perception of oppositely curved 3D structures.
Document Type: Conference Paper
Source: Scopus
Gouttard, S.a , Styner, M.a b , Joshi, S.c , Smith, R.G.a , Hazlett, H.C.a , Gerig, G.a b
Subcortical structure segmentation using probabilistic atlas priors
(2007) Progress in Biomedical Optics and Imaging - Proceedings of SPIE, 6512 (PART 2), art. no. 65122J, . Cited 5 times.
a Department of Psychiatry, University of North Carolina, Chapel Hill, NC, United States
b Department of Computer Science, University of North Carolina, Chapel Hill, NC, United States
c Deptartment of Biomedical Engineering, University of Utah, Salt Lake City, UT, United States
Abstract
The segmentation of the subcortical structures of the brain is required for many forms of quantitative neuroanatomy analysis. The volumetric and shape parameters of structures such as lateral ventricles, putamen, caudate, hippocampus, pallidus and amygdala are employed to characterize a disease or its evolution. This paper presents a fully automatic segmentation of these structures via a non-rigid registration of a probabilistic atlas prior and alongside a comprehensive validation. Our approach is based on an unbiased diffeomorphic atlas with probabilistic spatial priors built from a training set of MR images with corresponding manual segmentations. The atlas building computes an average image along with transformation fields mapping each training case to the average image. These transformation fields are applied to the manually segmented structures of each case in order to obtain a probabilistic map on the atlas. When applying the atlas for automatic structural segmentation, an MR image is first intensity inhomogeneity corrected, skull stripped and intensity calibrated to the atlas. Then the atlas image is registered to the image using an affine followed by a deformable registration matching the gray level intensity. Finally, the registration transformation is applied to the probabilistic maps of each structures, which are then thresholded at 0.5 probability. Using manual segmentations for comparison, measures of volumetric differences show high correlation with our results. Furthermore, the dice coefficient, which quantifies the volumetric overlap, is higher than 62% for all structures and is close to 80% for basal ganglia. The intraclass correlation coefficient computed on these same datasets shows a good inter-method correlation of the volumetric measurements. Using a dataset of a single patient scanned 10 times on 5 different scanners, reliability is shown with a coefficient of variance of less than 2 percents over the whole dataset. Overall, these validation and reliability studies show that our method accurately and reliably segments almost all structures. Only the hippocampus and amygdala segmentations exhibit relative low correlation with the manual segmentation in at least one of the validation studies, whereas they still show appropriate dice overlap coefficients.
Author Keywords
Segmentation; Shape; Shape analysis; Validation
Document Type: Conference Paper
Source: Scopus
Gilmore, J.H.a f , Lin, W.b , Corouge, I.c , Vetsa, Y.S.K.c , Smith, J.K.b , Kang, C.a d , Gu, H.a d , Hamer, R.M.a d , Lieberman, J.A.e , Gerig, G.a c
Early postnatal development of corpus callosum and corticospinal white matter assessed with quantitative tractography
(2007) American Journal of Neuroradiology, 28 (9), pp. 1789-1795. Cited 8 times.
a Schizophrenia Research Center, Department of Psychiatry, University of North Carolina, Chapel Hill, NC, United States
b Department of Radiology, University of North Carolina, Chapel Hill, NC, United States
c Department of Computer Science, University of North Carolina, Chapel Hill, NC, United States
d Department of Biostatistics, University of North Carolina, Chapel Hill, NC, United States
e Department of Psychiatry, Columbia University, New York, NY, United States
f Department of Psychiatry, CB# 7160, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-7160, United States
Abstract
BACKGROUND AND PURPOSE: The early postnatal period is perhaps the most dynamic phase of white matter development. We hypothesized that the early postnatal development of the corpus callosum and corticospinal tracts could be studied in unsedated healthy neonates by using novel approaches to diffusion tensor imaging (DTI) and quantitative tractography. MATERIALS AND METHODS: Isotropic 2 x 2 x 2 mm3 DTI and structural images were acquired from 47 healthy neonates. DTI and structural images were coregistered and fractional anisotropy (FA), mean diffusivity (MD), and normalized T1-weighted (T1W) and T2-weighted (T2W) signal intensities were determined in central midline and peripheral cortical regions of the white matter tracts of the genu and splenium of the corpus callosum and the central midbrain and peripheral cortical regions of the corticospinal tracts by using quantitative tractography. RESULTS: We observed that central regions exhibited lower MD, higher FA values, higher T1W intensity, and lower T2W intensity than peripheral cortical regions. As expected, MD decreased, FA increased, and T2W signal intensity decreased with increasing age in the genu and corticospinal tract, whereas there was no significant change in T1W signal intensity. The central midline region of the splenium fiber tract has a unique pattern, with no change in MD, FA, or T2W signal intensity with age, suggesting different growth trajectory compared with the other tracts. FA seems to be more dependent on tract organization, whereas MD seems to be more sensitive to myelination. CONCLUSIONS: Our novel approach may detect small regional differences and age-related changes in the corpus callosum and corticospinal white matter tracts in unsedated healthy neonates and may be used for future studies of pediatric brain disorders that affect developing white matter.
Document Type: Article
Source: Scopus
Sun, H.a , Yushkevich, P.A.a , Zhang, H.a , Cook, P.A.a , Duda, J.T.a , Simon, T.J.b , Gee, J.C.a
Shape-based normalization of the corpus callosum for DTI connectivity analysis
(2007) IEEE Transactions on Medical Imaging, 26 (9), pp. 1166-1178.
a Penn. Image Computing and Science Laboratory, Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, United States
b Cognitive Analysis and Brain Imaging Laboratory, M.I.N.D. Institute, University of California-Davis, Sacramento, CA 95817, United States
Abstract
The continuous medial representation (cm-rep) is an approach that makes it possible to model, normalize, and analyze anatomical structures on the basis of medial geometry. Having recently presented a partial differential equation (PDE)-based approach for 3-D cm-rep modeling [1], here we present an equivalent 2-D approach that involves solving an ordinary differential equation. This paper derives a closed form solution of this equation and shows how Pythagorean hodograph curves can be used to express the solution as a piecewise polynomial function, allowing efficient and robust medial modeling. The utility of the approach in medical image analysis is demonstrated by applying it to the problem of shape-based normalization of the midsagittal section of the corpus callosum. Using diffusion tensor tractography, we show that shapebased normalization aligns subrogions of the corpus callosum, defined by connectivity, more accurately than normalization based on volumetric registration. Furthermore, shape-based normalization helps increase the statistical power of group analysis in an experiment where features derived from diffusion tensor tractography are compared between two cohorts. These results suggest that cm-rep is an appropriate tool for normalizing the corpus callosum in white matter studies. © 2007 IEEE.
Author Keywords
Corpus callosum; Geometrical representation; Image analysis; Medial; Medial representation; Shape analysis; Skeleton
Document Type: Article
Source: Scopus
Huang, X.a g , Lee, Y.Z.b , McKeown, M.c , Gerig, G.d e , Gu, H.d , Weill Lin, P.b , Lewis, M.M.a , Ford, S.a , Tröster, A.I.a , Weinberger, D.R.f , Styner, M.d e
Asymmetrical ventricular enlargement in Parkinson's disease
(2007) Movement Disorders, 22 (11), pp. 1657-1660. Cited 2 times.
a Department of Neurology, School of Medicine, University of North Carolina, Chapel Hill, NC, United States
b Department of Radiology, School of Medicine, University of North Carolina, Chapel Hill, NC, United States
c Department of Medicine (Neurology), University of British Columbia (UBC), University Hospital, Vancouver, BC, Canada
d Department of Psychiatry, School of Medicine, University of North Carolina, Chapel Hill, NC, United States
e Department of Computer Science, University of North Carolina, Chapel Hill, NC, United States
f Clinical Brain Disorder Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States
g Department of Neurology, University of North Carolina, School of Medicine, Chapel Hill, NC 27599-7025, United States
Abstract
Parkinson's disease (PD) typically manifests with asymmetric motor symptom onset. Ventricular enlargement, a nonspecific measure of brain atrophy, has been associated with cognitive decline in PD, but not with motor symptom asymmetry. Asymmetrical ventricular enlargement on magnetic resonance images was explored in a monozygotic twin pair discordant for PD and in nine healthy monozygotic twin pairs. The left-right lateral ventricular volumetric difference of the PD-twin was greater than that of his twin and all other healthy twins, with the larger ventricle observed contralateral to the more symptomatic side. Moreover, the lateral ventricle asymmetry difference between twin pairs was significantly higher for the discordant PD-twin pair than for the healthy twin pairs. This is the first report to suggest the presence of asymmetrical ventricular enlargement in PD, findings that may be worthy of further study. © 2007 Movement Disorder Society.
Author Keywords
Motor impairment; Parkinson's disease; Ventricle; Volume asymmetry
Document Type: Article
Source: Scopus
Apostolova, L.G., Thompson, P.M.
Brain Mapping as a Tool to Study Neurodegeneration
(2007) Neurotherapeutics, 4 (3), pp. 387-400. Cited 9 times.
Department of Neurology, Laboratory of NeuroImaging, David Geffen School of Medicine, Los Angeles, CA 90095, United States
Abstract
Alzheimer's disease (AD) is the most common neurodegenerative disorder for those 65 years or older; it currently affects 4.5 million in the United States and is predicted to rise to 13.2 million by the year 2050. Neuroimaging and brain mapping techniques offer extraordinary power to understand AD, providing spatially detailed information on the extent and trajectory of the disease as it spreads in the living brain. Computational anatomy techniques, applied to large databases of brain MRI scans, reveal the dynamic sequence of cortical and hippocampal changes with disease progression and how these relate to cognitive decline and future clinical outcomes. People who are mildly cognitively impaired, in particular, are at a fivefold increased risk of imminent conversion to dementia, and they show specific structural brain changes that are predictive of imminent disease onset. We review the principles and key findings of several new methods for assessing brain degeneration, including voxel-based morphometry, tensor-based morphometry, cortical thickness mapping, hippocampal atrophy mapping, and automated methods for mapping ventricular anatomy. Applications to AD and other dementias are discussed, with a brief review of related findings in other neurological and neuropsychiatric illnesses, including epilepsy, HIV/AIDS, schizophrenia, and disorders of brain development. © 2007 The American Society for Experimental NeuroTherapeutics, Inc.
Author Keywords
Alzheimer's disease; Brain mapping; dementia; depression; human brain development; mild cognitive impairment; MRI; schizophrenia
Document Type: Article
Source: Scopus
Shamir, R.R.a , Freiman, M.a , Joskowicz, L.a , Zehavi, E.b , Spektor, S.b , Shoshan, Y.c
Surface-based preoperative CT/MRI to intraoperative face scan registration: A clinical study
(2007) Computer-Assisted Radiology and Surgery, 2 (1 SUPPL.), pp. S208-S210.
a School of Engineering and Computer Science, Hebrew University of Jerusalem, Jerusalem, Israel
b Mazor Surgical Technologies, Caesarea, Israel
c Department of Neurosurgery, School of Medicine, Hadassah University Hospital, Jerusalem, Israel
Abstract
We present a clinical study of surface-based registration between a preoperative CT/MRI of a patient head and an intraoperative surface scan of his face. The study was conducted on 14 patients that underwent neurosurgery with standard neuronavigation based on preoperative CT/MRI datasets. Intraoperatively, before the surgery started, surface scans of the patient faces were acquired with a surface scanner. After extracting face surface points in the upper region of the face from both datasets, the resulting point sets were aligned with a robust two-step rigid registration algorithm. The mean face registration error was 0.9 mm (STD 0.35 mm). The mean estimated target registration errors at60, 105, 150 mm from the face surface were 2.0, 3.2, 4.5 mm. These results indicate that surface-based face registration is clinically viable.
Author Keywords
Neurosurgery; Registration error; Surface-based rigid registration
Document Type: Conference Paper
Source: Scopus
Yushkevich, P.A.a , Detre, J.A.b , Mechanic-Hamilton, D.b , Fernández-Seara, M.A.b , Tang, K.Z.b , Hoang, A.b , Korczykowski, M.b , Zhang, H.a , Gee, J.C.a
Hippocampus-specific fMRI group activation analysis using the continuous medial representation
(2007) NeuroImage, 35 (4), pp. 1516-1530. Cited 12 times.
a Penn Image Computing and Science Laboratory (PICSL), Department of Radiology, University of Pennsylvania, 3600 Market St., Ste 370, Philadelphia, PA 19104, United States
b Center for Functional Neuroimaging, Department of Neurology, University of Pennsylvania, PA 19104, United States
Abstract
We present a new shape-based approach for regional group activation analysis in fMRI studies. The method restricts anatomical normalization, spatial smoothing and random effects statistical analysis to the space inside and around a structure of interest. Normalization involves finding intersubject correspondences between manually outlined masks, and it leverages the continuous medial representation, which makes it possible to extend surface-based shape correspondences to the space inside and outside of structures. Our approach is an alternative to whole-brain normalization in cases where the latter may fail due to anatomical variability or pathology. It also provides an opportunity to analyze the shape and thickness of structures concurrently with functional activation. We apply the technique to the hippocampus and evaluate it using data from a visual scene encoding fMRI study, where activation in the hippocampus is expected. We produce detailed statistical maps of hippocampal activation, as well as maps comparing activation inside and outside of the hippocampus. We find that random effects statistics computed by the new approach are more significant than those produced using the Statistical Parametric Mapping framework (Friston, K.J., Holmes, A.P., Worsley, K.J., Poline, J.-P., Firth, C.D., Frackowiak, R.S.J. 1994, Statistical parametric maps in functional imaging: a general linear approach. Human Brain Mapping, 2(4): 189-210) at low levels of smoothing, suggesting that greater specificity can be achieved by the new method without a severe tradeoff in sensitivity. © 2007 Elsevier Inc. All rights reserved.
Author Keywords
Functional neuroimaging; Hippocampus; Normalization; Random effects; Statistical Parametric Mapping
Document Type: Article
Source: Scopus
Xia, Y., Bettinger, K., Shen, L., Reiss, A.L.
Automatic segmentation of the caudate nucleus from human brain MR images
(2007) IEEE Transactions on Medical Imaging, 26 (4), pp. 509-517. Cited 11 times.
Center for Interdisciplinary Brain Sciences Research, Stanford University, School of Medicine, Stanford, CA 94305, United States
Abstract
We describe a knowledge-driven algorithm to automatically delineate the caudate nucleus (CN) region of the human brain from a magnetic resonance (MR) image. Since the lateral ventricles (LVs) are good landmarks for positioning the CN, the algorithm first extracts the LVs, and automatically localizes the CN from this information guided by anatomic knowledge of the structure. The face validity of the algorithm was tested with 55 high-resolution T1-weighted magnetic resonance imaging (MRI) datasets, and segmentation results were overlaid onto the original image data for visual inspection. We further evaluated the algorithm by comparing automated segmentation results to a "gold standard" established by human experts for these 55 MR datasets. Quantitative comparison showed a high intraclass correlation between the algorithm and expert as well as high spatial overlap between the regions-of-interest (ROIs) generated from the two methods. The mean spatial overlap ± standard deviation (defined by the intersection of the 2 ROIs divided by the union of the 2 ROIs) was equal to 0.873 ± 0.0234. The algorithm has been incorporated into a public domain software program written in Java and, thus, has the potential to be of broad benefit to neuroimaging investigators interested in basal ganglia anatomy and function. © 2007 IEEE.
Author Keywords
Caudate nucleus; Magnetic resonance imaging (MRI); Segmentation; Validation
Document Type: Article
Source: Scopus
Machado, A.M.C.a , Simon, T.J.b , Nguyen, V.b , McDonald-McGinn, D.M.c , Zackai, E.H.c , Gee, J.C.d
Corpus callosum morphology and ventricular size in chromosome 22q11.2 deletion syndrome
(2007) Brain Research, 1131 (1), pp. 197-210. Cited 11 times.
a Pontifical Catholic University of Minas Gerais, Av. Dom Jose Gaspar, 500, PPGEE, Belo Horizonte, MG 30535-610, Brazil
b M.I.N.D. Institute, University of California, Davis, CA 95817, United States
c Department of Clinical Genetics, Children's Hospital of Philadelphia, PA 19104-4399, United States
d Department of Radiology, University of Pennsylvania, PA 19104, United States
Abstract
In this paper, novel methods were used to map the corpus callosum morphology of children with chromosome 22q11.2 deletion syndrome in order to further investigate changes to that structure and to examine their possible effects on cognitive function. The callosal profiles were extracted from the centermost MRI midsagittal slice by supervised thresholding and the structure's boundary and midline were computed automatically. Difference analysis was based on non-rigid registration, in which a template image is warped to conform to the shape of each corpus callosum in the sample. Boundaries and midlines were registered to a template and the results used to determine the average callosal shapes for children with the deletion and for controls. Pointwise registration also enabled the detailed evaluation of callosal curvature, width, area and length. Significant differences between the two groups were found in shape, size and bending angle. Results showed group differences that were concentrated in the anterior part of the structure, more specifically in the rostrum, which was larger and longer in the group with the syndrome. Correlation analyses showed that ventricular enlargement does not fully account for callosal morphology differences in children with the deletion. However, areal measurements did reveal important relationships between changes in callosal morphology and cognitive function. These novel findings reveal intricate relationships between genetic and disease-specific factors in the callosal anatomy and the potential impact of those changes on cognitive functions. © 2006 Elsevier B.V. All rights reserved.
Author Keywords
Children; Chromosome 22q11.2 deletion syndrome; Cognition; Corpus callosum; Image registration; Morphology
Document Type: Article
Source: Scopus
Schoenemann, P.T.a b g , Gee, J.c , Avants, B.c , Holloway, R.L.d , Monge, J.b e , Lewis, J.f
Validation of plaster endocast morphology through 3D CT image analysis
(2007) American Journal of Physical Anthropology, 132 (2), pp. 183-192. Cited 4 times.
a Department of Behavioral Sciences, University of Michigan-Dearborn, Dearborn, MI 48128, United States
b Museum of Archaeology and Anthropology, University of Pennsylvania, Philadelphia, PA 19104, United States
c Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, United States
d Department of Anthropology, Columbia University, New York, NY 10027, United States
e Department of Anthropology, University of Pennsylvania, Philadelphia, PA 19104, United States
f Department of Anthropological Sciences, Stanford University, Stanford, CA 94305, United States
g Department of Behavioral Sciences, University of Michigan-Dearborn, 4026 CASL Building, 4901 Evergreen Road, Dearborn, MI 48128, United States
Abstract
A crucial component of research on brain evolution has been the comparison of fossil endocranial surfaces with modern human and primate endocrania. The latter have generally been obtained by creating endocasts out of rubber latex shells filled with plaster. The extent to which the method of production introduces errors in endocast replicas is unknown. We demonstrate a powerful method of comparing complex shapes in 3-dimensions (3D) that is broadly applicable to a wide range of paleoanthropological questions. Pairs of virtual endocasts (VEs) created from high-resolution CT scans of corresponding latex/plaster endocasts and their associated crania were rigidly registered (aligned) in 3D space for two Homo sapiens and two Pan troglodytes specimens. Distances between each cranial VE and its corresponding latex/plaster VE were then mapped on a voxel-by-voxel basis. The results show that between 79.7% and 91.0% of the voxels in the four latex/plaster VEs are within 2 mm of their corresponding cranial VEs surfaces. The average error is relatively small, and variation in the pattern of error across the surfaces appears to be generally random overall. However, inferior areas around the cranial base and the temporal poles were somewhat overestimated in both human and chimpanzee specimens, and the area overlaying Broca's area in humans was somewhat underestimated. This study gives an idea of the size of possible error inherent in latex/plaster endocasts, indicating the level of confidence we can have with studies relying on comparisons between them and, e.g., hominid fossil endocasts. © 2006 Wiley-Liss, Inc.
Author Keywords
Computed tomography; CT; Endocast; Validation
Document Type: Article
Source: Scopus
Corouge, I.a , Fletcher, P.T.b , Joshi, S.c , Gouttard, S.d , Gerig, G.a
Fiber tract-oriented statistics for quantitative diffusion tensor MRI analysis
(2006) Medical Image Analysis, 10 (5), pp. 786-798. Cited 28 times.
a Departments of Computer Science and Psychiatry, University of North Carolina, Chapel Hill, United States
b Scientific Computing and Imaging Institute, University of Utah, United States
c Department of Radiation Oncology, University of North Carolina, Chapel Hill, United States
d Department of Psychiatry, University of North Carolina, Chapel Hill, United States
Abstract
Quantitative diffusion tensor imaging (DTI) has become the major imaging modality to study properties of white matter and the geometry of fiber tracts of the human brain. Clinical studies mostly focus on regional statistics of fractional anisotropy (FA) and mean diffusivity (MD) derived from tensors. Existing analysis techniques do not sufficiently take into account that the measurements are tensors, and thus require proper interpolation and statistics of tensors, and that regions of interest are fiber tracts with complex spatial geometry. We propose a new framework for quantitative tract-oriented DTI analysis that systematically includes tensor interpolation and averaging, using nonlinear Riemannian symmetric space. A new measure of tensor anisotropy, called geodesic anisotropy (GA) is applied and compared with FA. As a result, tracts of interest are represented by the geometry of the medial spine attributed with tensor statistics (average and variance) calculated within cross-sections. Feasibility of our approach is demonstrated on various fiber tracts of a single data set. A validation study, based on six repeated scans of the same subject, assesses the reproducibility of this new DTI data analysis framework. © 2006 Elsevier B.V. All rights reserved.
Author Keywords
Diffusion tensor interpolation; Diffusion tensor statistics; DTI analysis; Fiber tract modeling
Document Type: Article
Source: Scopus
Zhang, H.a , Yushkevich, P.A.a , Alexander, D.C.b , Gee, J.C.a
Deformable registration of diffusion tensor MR images with explicit orientation optimization
(2006) Medical Image Analysis, 10 (5), pp. 764-785. Cited 32 times.
a Penn Image Computing and Science Laboratory (PICSL), Department of Radiology, University of Pennsylvania, 3600 Market Street, Suite 370, Philadelphia, PA 19104, United States
b Department of Computer Science, University College London, Gower Street, London, WC1E 6BT, United Kingdom
Abstract
In this paper, we present a novel deformable registration algorithm for diffusion tensor MR images that enables explicit optimization of tensor reorientation. The optimization seeks a piecewise affine transformation that divides the image domain into uniform regions and transform each region affinely. The objective function captures both the image similarity and the smoothness of the transformation across region boundaries. The image similarity enables explicit orientation optimization by incorporating tensor reorientation, which is necessary for warping diffusion tensor images. The objective function is formulated in a way that allows explicit implementation of analytic derivatives to drive fast and accurate optimization using the conjugate gradient method. By explicitly optimizing tensor reorientation, the algorithm is designed to take advantage of similarity measures comparing tensors as a whole. The optimal transformation is hierarchically refined in a subdivision framework. A comparison with affine registration for inter-subject normalization of 8 subjects shows that the proposed algorithm improves the alignment of several major white matter structures examined: the anterior thalamic radiations, the inferior fronto-occipital fasciculi, the corticospinal/corticobulbar tracts and the genu and the splenium of the corpus callosum. The alignment of white matter structures is assessed using a novel scheme of computing distances between the corresponding fiber bundles derived from tractography. © 2006 Elsevier B.V. All rights reserved.
Author Keywords
Diffusion tensor MRI; Registration; Spatial normalization; Tractography
Document Type: Article
Source: Scopus
Kubo, S.a , Levantini, E.b , Kobayashi, S.b , Kocher, O.c , Halmos, B.d , Tenen, D.G.b , Takahashi, M.a e
Three-dimensional magnetic resonance microscopy of pulmonary solitary tumors in transgenic mice
(2006) Magnetic Resonance in Medicine, 56 (3), pp. 698-703. Cited 4 times.
a Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States
b Department of Hematology and Oncology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States
c Department of Pathology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States
d Ireland Cancer Center, University Hospitals of Cleveland, Case Western Reserve University, Cleveland, OH, United States
e Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, 330 Brookline Ave., Boston, MA 02215, United States
Abstract
We attempted to accurately detect pulmonary solitary tumors and other complicated pulmonary disorders in aging inbred transgenic mice by cardiac- and respiratory-gated MR microscopy at 4.7 Tesla. A comparison of in vivo MR images with histological results demonstrated that submillimeter lung tumors and most of the nontumor lesions could be detected by screening with two-dimensional (2D) gradient echo (GRE) imaging. Subsequently performed 2D spin-echo (SE) imaging provided higher image contrast, which distinguished the tumors from the surrounding complications. On the 3D GRE images and the generated maximum intensity projection (MIP) and volume-rendered (VR) images, proper spatial localization of solitary tumors relative to the orientation of the pulmonary vessels was exhibited, and the tumor volume could also be measured. This promising method is noninvasive and has the potential to eventually replace invasive histopathology because it obviates the need to kill groups of animals at multiple time points. © 2006 Wiley-Liss, Inc.
Author Keywords
Cardiac-respiratory gating; Magnetic resonance microscopy; Solitary lung tumor; Spontaneous lung cancer; Transgenic mice
Document Type: Article
Source: Scopus
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