Using Convolutional Encoder Networks to Determine the Optimal Magnetic Resonance Image for the Automatic Segmentation of Multiple Sclerosis

Using Convolutional Encoder Networks to Determine the Optimal Magnetic Resonance Image for the Automatic Segmentation of Multiple Sclerosis

Multiple Sclerosis (MS) is a neuroinflammatory demyelinating disease that affects over 2,000,000 individuals worldwide. It is characterized by white matter lesions that are identified through the segmentation of magnetic resonance images (MRIs). Manual segmentation is very time-intensive because rad...

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Bibliographic Details
Main Authors: Shaurnav Ghosh, Marc Huo, Mst Shamim Ara Shawkat, Serena McCalla
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Series:Applied Sciences
Subjects:
convolutional encoder networks
convolutional neural networks
machine learning
magnetic resonance image
multiple sclerosis
segmentation
Online Access:https://www.mdpi.com/2076-3417/11/18/8335

Internet

https://www.mdpi.com/2076-3417/11/18/8335

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