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  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.