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Variation in tractography-derived measures in corticospinal tract reconstruction. скачать в хорошем качестве

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Variation in tractography-derived measures in corticospinal tract reconstruction.
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Variation in tractography-derived measures in corticospinal tract reconstruction.

This video is part of a project led by Dr. Farshid Sepehrband of the USC Mark and Mary Stevens Neuroimaging and Informatics Institute (INI). Students in the institute’s Master of Science in Neuroimaging and Informatics program’s Class of 2020 completed the project, which was accepted to OHBM 2020, the annual meeting of the Organization for Human Brain Mapping. The goal was to assess the effect of rater's manual choices on derived tractography, focusing on the corticospinal tract. Students were asked to draw the start point of the tractography (known as the seed point) and perform the tractography using a standardized algorithm. Then, they were asked to draw inclusion and exclusion masks to obtain a tract that best matched the neuroanatomical definition of the corticospinal tract. This video highlights the effect of these manual choices on the final tract. The bundle coloring signifies directionality, with left-right fibers labeled red, front-back fibers labeled green, and vertically oriented fibers labeled blue. Diffusion MRI is a powerful tool for mapping the microstructure and connectivity of the human brain. It entails the combination of MRI scanning with time-varying magnetic field gradients to characterize spatial patterns of water molecule diffusion, which are reflected by signal attenuation due to phase dispersion in the gradient direction. Given the image data from the scanner, computational techniques can be used to model or summarize the diffusion signals to obtain image parameter maps that reflect underlying tissue microstructure properties. Beyond these quantitative maps, we can also use diffusion MRI tractography to explore the large-scale organization of the brain. Tractography uses diffusion MRI estimates of fiber orientations to reconstruct geometric models of the large-scale groupings of axons, known as fiber bundles, that connect cortical and subcortical brain areas.

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