A comparison of supervised machine learning algorithms and feature vectors for MS lesion segmentation using multimodal structural MRI.

A comparison of supervised machine learning algorithms and feature vectors for MS lesion segmentation using multimodal structural MRI.

Machine learning is a popular method for mining and analyzing large collections of medical data. We focus on a particular problem from medical research, supervised multiple sclerosis (MS) lesion segmentation in structural magnetic resonance imaging (MRI). We examine the extent to which the choice of...

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Bibliographic Details
Main Authors: Elizabeth M Sweeney, Joshua T Vogelstein, Jennifer L Cuzzocreo, Peter A Calabresi, Daniel S Reich, Ciprian M Crainiceanu, Russell T Shinohara
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2014-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC4004572?pdf=render

Internet

http://europepmc.org/articles/PMC4004572?pdf=render

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