An automated method for segmenting white matter lesions through multi-level morphometric feature classification with application to lupus

An automated method for segmenting white matter lesions through multi-level morphometric feature classification with application to lupus

We demonstrate an automated, multi-level method to segment white matter brain lesions and apply it to lupus. The method makes use of local morphometric features based on multiple MR sequences, including T1-weighted, T2-weighted, and Fluid Attenuated Inversion Recovery. After preprocessing, including...

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Bibliographic Details
Main Authors: Mark Scully, Blake Anderson, Terran Lane, Charles Gasparovic, Vince Magnotta, Wilmer Sibbitt, Carlos Roldan, Ron Kikinis, Henry Jeremy Bockholt
Format: Article
Language:English
Published: Frontiers Media S.A. 2010-04-01
Series:Frontiers in Human Neuroscience
Subjects:
Classification
machine learning
lesion
lupus
Method
segmentation
Online Access:http://journal.frontiersin.org/Journal/10.3389/fnhum.2010.00027/full

Internet

http://journal.frontiersin.org/Journal/10.3389/fnhum.2010.00027/full

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