Deep Learning With Diffusion Basis Spectrum Imaging For Classification Of Multiple Sclerosis Lesions

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The MRC Centre was established in 2008 as a joint partnership between the UCL Institute of Neurology, Queen Square, the UC L Institute of Child Health and the University of Newcastle upon

Understanding the pathophysiology of cognitive changes in MS

multiple sclerosis. Lancet Neurol 2015; 14(3): 302 317. 4. Mainero C, Louapre C, Govindarajan ST, et al. A gradient in cortical pathology in multiple sclerosis by in vivo quantitative 7 T imaging. Brain 2015; 138 (Pt. 4): 932 945. 5. Herranz E, Gianni C, Louapre C, et al. Neuroinflammatory component of gray matter pathology in multiple

Improved algorithm for multiple sclerosis diagnosis in MRI

Zhezhog [12] tested by combining a deep learning algorithm using deep neural network (DNN) with Diffusion Basis Spectrum Imaging (DBSI). Thirty eight MS patients were scanned with diffusion-weighted imaging, magnetisation transfer imaging and standard conventional MRI sequences. The optimised DNN with

OMB No. 0925-0046, Biographical Sketch Format Page

A Deep Learning based Diffusion Histology Imaging for Mulitple Scrolesis Lesion Classification, Annals of Clinical and Translational Neurology, 2020. doi: 10.1002/acn3.51037.