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TractLearn: a geodesic learning framework for quantitative analysis of brain bundles
2020-05-29
radiology and imaging
Title + abstract only
View on medRxiv
Show abstract
Deep learning-based convolutional neural networks have recently proved their efficiency in providing fast segmentation of major brain fascicles structures, based on diffusion-weighted imaging. The quantitative analysis of brain fascicles then relies on metrics either coming from the tractography process itself or from each voxel along the bundle. Statistical detection of abnormal voxels in the context of disease usually relies on univariate and multivariate statistics models, such as the Genera...
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