Tract-Based Morphometry: White Matter Tract Clustering and Correspondence in Populations

Lauren O'Donnell
Harvard University

The ability to perform statistical analysis of the brain's white matter connections (fiber tracts) has applications in neuroscience and in the study of disease. A popular approach for white matter analysis is the quantification of parameters derived from DTI tractography. We begin the presentation with an overview of white matter fiber tract anatomy as seen in streamline tractography data. Then we address two problems that must be solved to perform group analysis of DTI data within a fiber tract of interest. The tract must first be identified (segmented) in all subjects. Second, to localize group differences to a region within the tract, a common coordinate system must be generated for that tract in all subjects. Our tract-based morphometry analysis pipeline performs segmentation based on learning a model of common white matter structures in the
group, followed by statistical analysis of data along fiber tracts. We explain our approach to the segmentation and coordinate system problems, and we provide pointers to related methods.

Audio (MP3 File, Podcast Ready) Presentation (PDF File)

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