Project: 4D Analysis of White-Matter Diffusion


Subject-specific analysis of image data often includes comparison of follow-up to baseline, serial staging of progress of disease, or monitoring therapeutic intervention. Key methodological components are intra-subject registration of the set of scans, and analysis of geometric deformations and appearance changes. In DWI data, such analysis includes deformation of the set of DWI with associated correction of tensor orientation or local ODF adjustment. In addition, scalar invariants such as FA, MD, axial, and radial diffusivities have to be compared in regions or along tracts at corresponding anatomical locations.

With the availability of longitudinal or serial 3D image data for each subject, the image processing gets new opportunities for spatiotemporal processing of 4D datasets. The conventional cross-sectional comparison between subjects are groups at various time points is replaced by comparison and analysis of subject-specific change trajectories. In this project, we focus on the development of longitudinal analysis of DTI.

 

theme-diffusion

 

DTI population atlas: Left Tensor field of atlas computed over 86 subjects: Middle: FA map calculated from tensor atlas. Right: Typical fiber bundles used in this study. Mid corpus callosum, sensory-motor and genu tracts are color-coded with FA, with [0 · · · 1] ranging from dark blue over yellow to red.

 

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