Object-Based Strategy for Morphometry of the Cerebral Cortex

Most of the approaches dedicated to automatic morphometry rely on a point-by-point strategy based on warping each brain towards a reference coordinate system. In this paper, we describe an alternative object-based strategy dedicated to the cortex. This strategy relies on an artificial neuroanatomist performing automatic recognition of the main cortical sulci and parcellation of the cortical surface into gyral patches. A set of shape descriptors, which can be compared across subjects, is then attached to the sulcus and gyrus related objects segmented by this process. The framework is used to perform a study of 142 brains of the ICBM database. This study reveals some correlates of handedness on the size of the sulci located in motor areas, which seem to be beyond the scope of the standard voxel based morphometry.

[1]  Christopher J. Taylor,et al.  Using Local Geometry to Build 3D Sulcal Models , 1999, IPMI.

[2]  Karl J. Friston,et al.  A Voxel-Based Morphometric Study of Ageing in 465 Normal Adult Human Brains , 2001, NeuroImage.

[3]  A. Toga,et al.  Mapping brain asymmetry , 2003, Nature Reviews Neuroscience.

[4]  Jean-Francois Mangin,et al.  Multisubject Non-rigid Registration of Brain MRI Using Intensity and Geometric Features , 2001, MICCAI.

[5]  Isabelle Bloch,et al.  A Mean Curvature Based Primal Sketch to Study the Cortical Folding Process from Antenatal to Adult Brain , 2001, MICCAI.

[6]  Karl J. Friston,et al.  Spatial registration and normalization of images , 1995 .

[7]  Michel Vidal-Naquet,et al.  Visual features of intermediate complexity and their use in classification , 2002, Nature Neuroscience.

[8]  A M Dale,et al.  Measuring the thickness of the human cerebral cortex from magnetic resonance images. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[9]  P. Roland,et al.  Comparison of spatial normalization procedures and their impact on functional maps , 2002, Human brain mapping.

[10]  D. Louis Collins,et al.  Automated extraction and variability analysis of sulcal neuroanatomy , 1999, IEEE Transactions on Medical Imaging.

[11]  William M. Wells,et al.  Medical Image Computing and Computer-Assisted Intervention — MICCAI’98 , 1998, Lecture Notes in Computer Science.

[12]  山浦 晶.  Atlas of the Cerebral Sulci, Michio Ono, Stefan Kubik and Chad D. Abernathey著, Georg Thieme Verlag, Stuttgart, New York 1990(らいぶらりい) , 1992 .

[13]  Michel Desvignes,et al.  Detection and Statistical Analysis of Human Cortical Sulci , 1999, NeuroImage.

[14]  M. Raichle,et al.  A Stereotactic Method of Anatomical Localization for Positron Emission Tomography , 1985, Journal of computer assisted tomography.

[15]  A. Schleicher,et al.  Asymmetry in the Human Motor Cortex and Handedness , 1996, NeuroImage.

[16]  Paul M. Thompson,et al.  A surface-based technique for warping three-dimensional images of the brain , 1996, IEEE Trans. Medical Imaging.

[17]  J. Régis,et al.  Generic model for the localization of the cerebral cortex and preoperative multimodal integration in epilepsy surgery. , 1995, Stereotactic and functional neurosurgery.

[18]  J Mazziotta,et al.  A probabilistic atlas and reference system for the human brain: International Consortium for Brain Mapping (ICBM). , 2001, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[19]  W. Welker.  Why Does Cerebral Cortex Fissure and Fold , 1990 .

[20]  Christos Davatzikos,et al.  Finding parametric representations of the cortical sulci using an active contour model , 1997, Medical Image Anal..

[21]  D. V. van Essen,et al.  A tension-based theory of morphogenesis and compact wiring in the central nervous system. , 1997, Nature.

[22]  D. V. van Essen,et al.  Functional and structural mapping of human cerebral cortex: solutions are in the surfaces. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[23]  Jelliffe.  Vergleichende Lokalisationslehre der Grosshirnrinde , 1910 .

[24]  小野 道夫,et al.  Atlas of the Cerebral Sulci , 1990 .

[25]  Computer-Assisted Intervention,et al.  Medical Image Computing and Computer-Assisted Intervention – MICCAI’99 , 1999, Lecture Notes in Computer Science.

[26]  I. Biederman.  Recognition-by-components: a theory of human image understanding. , 1987, Psychological review.

[27]  Isabelle Bloch,et al.  Gyral Parcellation of the Cortical Surface Using Geodesic Voronoï Diagrams , 2002, MICCAI.

[28]  Alan C. Evans,et al.  Structural asymmetries in the human brain: a voxel-based statistical analysis of 142 MRI scans. , 2001, Cerebral cortex.

[29]  A. Toga,et al.  New approaches in brain morphometry. , 2002, The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry.

[30]  Jerry L Prince,et al.  Automated Sulcal Segmentation Using Watersheds on the Cortical Surface , 2002, NeuroImage.

[31]  Isabelle Bloch,et al.  From 3D magnetic resonance images to structural representations of the cortex topography using topology preserving deformations , 1995, Journal of Mathematical Imaging and Vision.

[32]  A. Dale,et al.  High‐resolution intersubject averaging and a coordinate system for the cortical surface , 1999, Human brain mapping.

[33]  Keith J. Worsley,et al.  The Geometry of Random Images , 1996 .

[34]  D. Collins,et al.  Automatic 3D Intersubject Registration of MR Volumetric Data in Standardized Talairach Space , 1994, Journal of computer assisted tomography.

[35]  I. Johnsrude,et al.  The problem of functional localization in the human brain , 2002, Nature Reviews Neuroscience.

[36]  K. Amunts,et al.  Interhemispheric asymmetry of the human motor cortex related to handedness and gender , 2000, Neuropsychologia.

[37]  Robert T. Schultz,et al.  A New Approach to 3D Sulcal Ribbon Finding from MR Images , 1999, MICCAI.

[38]  Edgar M. Housepian.  Atlas d'anatomie stereotaxique du telencephale. , 1968 .

[39]  D. Louis Collins,et al.  Retrospective evaluation of intersubject brain registration , 2003, IEEE Transactions on Medical Imaging.

[40]  Alan C. Evans,et al.  Automated 3-D Extraction of Inner and Outer Surfaces of Cerebral Cortex from MRI , 2000, NeuroImage.

[41]  Ron Kikinis,et al.  Medical Image Computing and Computer-Assisted Intervention — MICCAI 2002 , 2002, Lecture Notes in Computer Science.

[42]  C. Davatzikos,et al.  Morphometric Analysis of Cortical Sulci Using Parametric Ribbons: A Study of the Central Sulcus , 2002, Journal of computer assisted tomography.

[43]  D. Louis Collins,et al.  Non-linear Cerebral Registration with Sulcal Constraints , 1998, MICCAI.

[44]  Wiro J. Niessen,et al.  Medical Image Computing and Computer-Assisted Intervention – MICCAI 2001 , 2001, Lecture Notes in Computer Science.

[45]  T. Poggio,et al.  Neural mechanisms of object recognition , 2002, Current Opinion in Neurobiology.

[46]  Jean-Francois Mangin,et al.  Automatic recognition of cortical sulci of the human brain using a congregation of neural networks , 2002, Medical Image Anal..

[47]  R. Woods,et al.  Mathematical/computational challenges in creating deformable and probabilistic atlases of the human brain , 2000, Human brain mapping.

[48]  Gabriele Lohmann,et al.  Automatic labelling of the human cortical surface using sulcal basins , 2000, Medical Image Anal..

[49]  Christian Barillot,et al.  Modeling Cortical Sulci with Active Ribbons , 1997, Int. J. Pattern Recognit. Artif. Intell..

[50]  D. Louis Collins,et al.  Retrospective Evaluation of Inter-subject Brain Registration , 2001, MICCAI.

[51]  Donald Geman,et al.  Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images , 1984 .

[52]  L. White,et al.  Cerebral asymmetry and handedness , 1994, Nature.

[53]  Karl J. Friston,et al.  Voxel-Based Morphometry—The Methods , 2000, NeuroImage.

[54]  Nick C Fox,et al.  Computer-assisted imaging to assess brain structure in healthy and diseased brains , 2003, The Lancet Neurology.

[55]  L. White,et al.  Structure of the human sensorimotor system. II: Lateral symmetry. , 1997, Cerebral cortex.