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Proceedings Paper

Early detection of Alzheimer's disease using histograms in a dissimilarity-based classification framework
Author(s): Anne Luchtenberg; Rita Simões; Anne-Marie van Cappellen van Walsum; Cornelis H. Slump
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Paper Abstract

Classification methods have been proposed to detect early-stage Alzheimer’s disease using Magnetic Resonance images. In particular, dissimilarity-based classification has been applied using a deformation-based distance measure. However, such approach is not only computationally expensive but it also considers large-scale alterations in the brain only. In this work, we propose the use of image histogram distance measures, determined both globally and locally, to detect very mild to mild Alzheimer’s disease. Using an ensemble of local patches over the entire brain, we obtain an accuracy of 84% (sensitivity 80% and specificity 88%).

Paper Details

Date Published: 18 March 2014
PDF: 10 pages
Proc. SPIE 9035, Medical Imaging 2014: Computer-Aided Diagnosis, 903502 (18 March 2014); doi: 10.1117/12.2042670
Show Author Affiliations
Anne Luchtenberg, Univ. Twente (Netherlands)
Rita Simões, MIRA Institute for Biomedical Technology and Technical Medicine, Univ. Twente (Netherlands)
Anne-Marie van Cappellen van Walsum, MIRA Institute for Biomedical Technology and Technical Medicine, Univ. Twente (Netherlands)
Radboud Univ. Nijmegen Medical Ctr. (Netherlands)
Cornelis H. Slump, MIRA Institute for Biomedical Technology and Technical Medicine, Univ. Twente (Netherlands)


Published in SPIE Proceedings Vol. 9035:
Medical Imaging 2014: Computer-Aided Diagnosis
Stephen Aylward; Lubomir M. Hadjiiski, Editor(s)

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