文章基本信息

标题：Classifying Dementia Using Local Binary Patterns from Different Regions in Magnetic Resonance Images
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作者：Ketil Oppedal ; Trygve Eftestøl ; Kjersti Engan 等
期刊名称：International Journal of Biomedical Imaging
印刷版ISSN：1687-4188
电子版ISSN：1687-4196
出版年度：2015
卷号：2015
DOI：10.1155/2015/572567
出版社：Hindawi Publishing Corporation
摘要：Dementia is an evolving challenge in society, and no disease-modifying treatment exists. Diagnosis can be demanding and MR imaging may aid as a noninvasive method to increase prediction accuracy. We explored the use of 2D local binary pattern (LBP) extracted from FLAIR and T1 MR images of the brain combined with a Random Forest classifier in an attempt to discern patients with Alzheimer's disease (AD), Lewy body dementia (LBD), and normal controls (NC). Analysis was conducted in areas with white matter lesions (WML) and all of white matter (WM). Results from 10-fold nested cross validation are reported as mean accuracy, precision, and recall with standard deviation in brackets. The best result we achieved was in the two-class problem NC versus AD