A deep learning-based approach for simultaneously segmenting T2 lesions and T1 hypointensities in multiple sclerosis regulatory clinical trials (4379)-Reference-Cited by-同舟云学术

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A deep learning-based approach for simultaneously segmenting T2 lesions and T1 hypointensities in multiple sclerosis regulatory clinical trials (4379)

Published:2021-04-13 Issue:15_supplement Volume:96 Page:
ISSN:0028-3878
Container-title:Neurology
language:en
Short-container-title:Neurology

Author:

Bergsland Niels¹²,Jakimovski Dejan¹,Ramasamy Deepa¹,Zivadinov Robert¹³,Dwyer Michael¹

Affiliation:

1. Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School

2. IRCCS, Fondazione Don Carlo Gnocchi ONLUS

3. Center for Biomedical Imaging at Clinical Translational Research Center, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Neurology (clinical)

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Dynamic disability measures decrease the clinico-radiological gap in people with severely affected multiple sclerosis;Multiple Sclerosis and Related Disorders;2024-07

2. Glial cell injury and atrophied lesion volume as measures of chronic multiple sclerosis inflammation;Journal of the Neurological Sciences;2024-06

3. Human restricted CHRFAM7A gene increases brain efficiency;Frontiers in Neuroscience;2024-04-22

4. Cognitive function in severe progressive multiple sclerosis;Brain Communications;2024

5. Auditory Test of Processing Speed: Preliminary validation of a smartphone-based test of mental speed;Multiple Sclerosis Journal;2023-10-16

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