Reducing the impact of white matter lesions on automated measures of brain gray and white matter volumes

Purpose: To develop an automated lesion‐filling technique (LEAP; LEsion Automated Preprocessing) that would reduce lesion‐associated brain tissue segmentation bias (which is known to affect automated brain gray [GM] and white matter [WM] tissue segmentations in people who have multiple sclerosis), a...

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Bibliographic Details

Published in:	Journal of magnetic resonance imaging Vol. 32; no. 1; pp. 223 - 228
Main Authors:	Chard, Declan T., Jackson, Jonathan S., Miller, David H., Wheeler-Kingshott, Claudia A.M.
Format:	Journal Article
Language:	English
Published:	Hoboken Wiley Subscription Services, Inc., A Wiley Company 01.07.2010
Subjects:	brain Brain - anatomy & histology Computer Simulation error correction Humans Image Processing, Computer-Assisted - methods Imaging, Three-Dimensional - methods Magnetic Resonance Imaging - methods MRI multiple sclerosis Reference Values segmentation errors white matter lesions
ISSN:	1053-1807, 1522-2586, 1522-2586
Online Access:	Get full text
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