期刊
NEUROIMAGE
卷 52, 期 4, 页码 1261-1267出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2010.05.029
关键词
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资金
- NSERC/MITACS
- endMS society of Canada
- NIH, National Center for Research Resources [R01 RR021885]
- National Institute of Biomedical Imaging and Bioengineering [R01 EB008015]
Several methods exist and are frequently used to quantify grey matter (GM) atrophy in multiple sclerosis (MS). Fundamental to all available techniques is the accurate segmentation of GM in the brain, a difficult task confounded even further by the pathology present in the brains of MS patients. In this paper, we examine the segmentations of six different automated techniques and compare them to a manually defined reference standard. Results demonstrate that, although the algorithms perform similarly to manual segmentations of cortical GM, severe shortcomings are present in the segmentation of deep GM structures. This deficiency is particularly relevant given the current interest in the role of GM in MS and the numerous reports of atrophy in deep GM structures. (C) 2010 Elsevier Inc. All rights reserved.
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