期刊
JOURNAL OF NEUROSCIENCE METHODS
卷 194, 期 2, 页码 380-385出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.jneumeth.2010.10.019
关键词
Shape; Multidimensional scaling; Alzheimer's disease; Mini Mental State Exam; Image registration
资金
- Ministry of Education, Science and Technology [20100023233]
- Business for Cooperative R&D between Industry, Academy, and Research Institute [0850110]
- Ministry of Knowledge Economy of Korea [10030091]
- National Institutes of Health [U01 AG024904]
- Alzheimer's Disease Neuroimaging Initiative (ADNI)
- National Institute on Aging
- National Institute of Biomedical Imaging and Bioengineering
- Abbott, AstraZeneca AB
- Bayer Schering Pharma AG
- Bristol-Myers Squibb
- Eisai Global Clinical Development, Elan Corporation, Genentech, GE Healthcare
- GlaxoSmithKline, Infogenetics
- Johnson and Johnson, Eli Lilly and Co.
- Medpace, Inc.
- Merck and Co., Inc.
- Novartis AG
- Pfizer Inc.
- F. Hoffman-La Roche, Schering-Plough. Synarc, Inc.
- Alzheimer's Association and Alzheimer's Drug Discovery Foundation
- U.S. Food and Drug Administration
- NIH [P30 AG010129, K01 AG030514]
- Dana Foundation
- Korea Evaluation Institute of Industrial Technology (KEIT) [10030091] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
- National Research Foundation of Korea [2010-0023233] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
Today, high-resolution MRI scans are able to reveal even the fine details of brain structure. Several methods have been developed to quantify shape differences specific to scans of diseased brains. We have developed a novel method for quantifying shape information based on multidimensional scaling (MDS), a well-known statistical tool. Multidimensional scaling uses distance measures computed from pair-wise image registration of the training set. Image registration establishes spatial correspondence between scans in order to compare them in the same spatial framework. Our novel method has several advantages, including robustness to errors in registrations. Applying our method to 44 brain MR's showed clear separation between normal and Alzheimer scans. Using our method as basis for classification between normal and Alzheimer scans yielded better performance results compared with using the volume of hippocampus as basis for classification. We also devised a simple measure derived from the MDS approach that was shown to correlate with the Mini Mental State Examination (MMSE), a well-known cognitive test for Alzheimer's disease. (C) 2010 Elsevier B.V. All rights reserved.
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