期刊
NEUROIMAGE
卷 44, 期 1, 页码 99-111出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2008.08.045
关键词
Computational anatomy; Voxel-based morphometry; Alzheimer's disease; Threshold masking; Analysis mask
资金
- EPSRC
- Wellcome Trust Intermediate Clinical Fellowship
- UK Medical Research Council
- Dementia Research Centre is an Alzheimer's Research Trust Co- ordinating Centre
- UCLH/ UCL
- Department of Health's NIHR Biomedical Research Centres
- MRC [G0401247, G0601846] Funding Source: UKRI
- Medical Research Council [G0401247, G0601846] Funding Source: researchfish
There is great interest in using automatic computational neuroanatomy tools to study ageing and neurodegenerative disease. Voxel-based morphometry (VBM) is one of the most widely used of such techniques. VBM performs voxel-wise statistical analysis of smoothed spatially normalised segmented Magnetic Resonance Images. There are several reasons why the analysis should include only voxels within a certain mask. We show that one of the most commonly used strategies for de. ning this mask runs a major risk of excluding from the analysis precisely those voxels where the subjects' brains were most vulnerable to atrophy. We investigate the issues related to mask construction, and recommend the use of alternative strategies which greatly decrease this danger of false negatives. (C) 2008 Elsevier Inc. All rights reserved.
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