Corpus Callosum Subdivision Based on a Probabilistic Model of Inter-hemispheric Connectivity

Statistical shape analysis has become of increasing interest to the neuroimaging community due to its potential to locate morphological changes. In this paper, we present the a novel combination of shape analysis and Diffusion Tensor Image (DTI) Tractography to the computation of a probabilistic, model based corpus callosum (CC) subdivision. The probabilistic subdivision is based on the distances of arc-length parameterized corpus callosum contour points to trans-callosal DTI fibers associated with an automatic lobe subdivision. Our proposed subdivision method is automatic and reproducible, Its results are more stable than the Witelson subdivision scheme or other commonly applied schemes based on the CC bounding box. We present the application of our subdivision method to a small scale study of regional CC area growth in healthy subjects from age 2 to 4 years.

[1]  David H. Laidlaw,et al.  Visualization and image processing of tensor fields , 2006 .

[2]  Robert J. Zatorre,et al.  Sexual Dimorphism in the Corpus Callosum: Methodological Considerations in MRI Morphometry , 2001, NeuroImage.

[3]  S. F. Witelson.  Hand and sex differences in the isthmus and genu of the human corpus callosum. A postmortem morphological study. , 1989, Brain : a journal of neurology.

[4]  Christos Davatzikos,et al.  A Framework for Callosal Fiber Distribution Analysis , 2002, NeuroImage.

[5]  Alejandro F Frangi,et al.  Automatic construction of 3-D statistical deformation models of the brain using nonrigid registration , 2003, IEEE Transactions on Medical Imaging.

[6]  Koenraad Van Leemput,et al.  Automated model-based tissue classification of MR images of the brain , 1999, IEEE Transactions on Medical Imaging.

[7]  Alejandro F. Frangi,et al.  Automatic Construction of 3D Statistical Deformation Models of the Brain using Non-Rigid Registration , 2003, IEEE Trans. Medical Imaging.

[8]  J. Sweeney,et al.  Abnormalities of the corpus callosum in first episode, treatment naive schizophrenia , 2002, Journal of neurology, neurosurgery, and psychiatry.

[9]  Guido Gerig,et al.  Unbiased diffeomorphic atlas construction for computational anatomy , 2004, NeuroImage.

[10]  A. Toga,et al.  Mapping morphology of the corpus callosum in schizophrenia. , 2000, Cerebral cortex.

[11]  Guido Gerig,et al.  Segmentation of 2-D and 3-D objects from MRI volume data using constrained elastic deformations of flexible Fourier contour and surface models , 1996, Medical Image Anal..

[12]  Terry M. Peters,et al.  Medical Image Computing and Computer-Assisted Intervention - MICCAI 2003 , 2003, Lecture Notes in Computer Science.

[13]  Alan C. Evans,et al.  Growth patterns in the developing brain detected by using continuum mechanical tensor maps , 2000, Nature.

[14]  Brian B. Avants,et al.  Anatomy-Based Visualizations of Diffusion Tensor Images of Brain White Matter , 2006, Visualization and Processing of Tensor Fields.

[15]  John H. Gilmore,et al.  Quantitative Analysis of White Matter Fiber Properties along Geodesic Paths , 2003, MICCAI.