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Multiple sclerosis (MS) lesions are heterogeneous with regard to inflammation, demyelination, axonal injury, and neuronal loss. We previously developed a diffusion basis spectrum imaging (DBSI) technique to better address MS… Click to show full abstract
Multiple sclerosis (MS) lesions are heterogeneous with regard to inflammation, demyelination, axonal injury, and neuronal loss. We previously developed a diffusion basis spectrum imaging (DBSI) technique to better address MS lesion heterogeneity. We hypothesized that the profiles of multiple DBSI metrics can identify lesion‐defining patterns. Here we test this hypothesis by combining a deep learning algorithm using deep neural network (DNN) with DBSI and other imaging methods.
Keywords:
basis spectrum;
spectrum imaging;
deep learning;
multiple sclerosis;
sclerosis lesions;
diffusion basis
Journal Title: Annals of Clinical and Translational Neurology
Year Published: 2020
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Journal Title: Annals of Clinical and Translational Neurology
Year Published: 2020
Link to full text (if available)
Share on Social Media: Sign Up to like & get
recommendations!