Abstract
We present an automated approach to the problem of connectivity-based partitioning of brain structures using diffusion imaging. White-matter fibres connect different areas of the brain, allowing them to interact with each other. Diffusion-tensor MRI measures the orientation of white-matter fibres in vivo, allowing us to perform connectivity-based partitioning non-invasively. Our new approach leverages atlas-based segmentation to automate anatomical labeling of the cortex. White-matter connectivities are inferred using a probabilistic tractography algorithm that models crossing pathways explicitly. The method is demonstrated with the partitioning of the corpus callosum of eight healthy subjects. © Springer-Verlag Berlin Heidelberg 2005.
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CITATION STYLE
Cook, P. A., Zhang, H., Avants, B. B., Yushkevich, P., Alexander, B. C., Gee, J. C., … Thompson, A. J. (2005). An automated approach to connectivity-based partitioning of brain structures. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3749 LNCS, pp. 164–171). Springer Verlag. https://doi.org/10.1007/11566465_21
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