Applying Deep Learning to Accelerated Clinical Brain Magnetic Resonance Imaging for Multiple Sclerosis

Applying Deep Learning to Accelerated Clinical Brain Magnetic Resonance Imaging for Multiple Sclerosis

Background: Magnetic resonance (MR) scans are routine clinical procedures for monitoring people with multiple sclerosis (PwMS). Patient discomfort, timely scheduling, and financial burden motivate the need to accelerate MR scan time. We examined the clinical application of a deep learning (DL) model...

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Bibliographic Details
Main Authors: Ashika Mani, Tales Santini, Radhika Puppala, Megan Dahl, Shruthi Venkatesh, Elizabeth Walker, Megan DeHaven, Cigdem Isitan, Tamer S. Ibrahim, Long Wang, Tao Zhang, Enhao Gong, Jessica Barrios-Martinez, Fang-Cheng Yeh, Robert Krafty, Joseph M. Mettenburg, Zongqi Xia
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-09-01
Series:Frontiers in Neurology
Subjects:
multiple sclerosis
deep learning
artificial intelligence
magnetic resonance imaging
accelerated acquisition
patient-reported outcome (PRO)
Online Access:https://www.frontiersin.org/articles/10.3389/fneur.2021.685276/full

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