3D U-Net for automated detection of multiple sclerosis lesions: utility of transfer learning from other pathologies

3D U-Net for automated detection of multiple sclerosis lesions: utility of transfer learning from other pathologies

Background and purposeDeep learning algorithms for segmentation of multiple sclerosis (MS) plaques generally require training on large datasets. This manuscript evaluates the effect of transfer learning from segmentation of another pathology to facilitate use of smaller MS-specific training datasets...

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Bibliographic Details
Main Authors: Stephen G. Wahlig, Pierre Nedelec, David A. Weiss, Jeffrey D. Rudie, Leo P. Sugrue, Andreas M. Rauschecker
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-10-01
Series:Frontiers in Neuroscience
Subjects:
multiple sclerosis
demyelination
deep learning
transfer learning
segmentation
Online Access:https://www.frontiersin.org/articles/10.3389/fnins.2023.1188336/full

Internet

https://www.frontiersin.org/articles/10.3389/fnins.2023.1188336/full

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