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Characterizing brain patterns in conversion from mild cognitive impairment (MCI) to Alzheimer's disease
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Paper Abstract

Structural Magnetic Resonance (MR) brain images should provide quantitative information about the stage and progression of Alzheimer’s disease. However, the use of MRI is limited and practically reduced to corroborate a diagnosis already performed with neuropsychological tools. This paper presents an automated strategy for extraction of relevant anatomic patterns related with the conversion from mild cognitive impairment (MCI) to Alzheimer’s disease (AD) using T1-weighted MR images. The process starts by representing each of the possible classes with models generated from a linear combination of volumes. The difference between models allows us to establish which are the regions where relevant patterns might be located. The approach searches patterns in a space of brain sulci, herein approximated by the most representative gradients found in regions of interest defined by the difference between the linear models. This hypothesis is assessed by training a conventional SVM model with the found relevant patterns under a leave-one-out scheme. The resultant AUC was 0.86 for the group of women and 0.61 for the group of men.

Paper Details

Date Published: 17 November 2017
PDF: 8 pages
Proc. SPIE 10572, 13th International Conference on Medical Information Processing and Analysis, 105720I (17 November 2017); doi: 10.1117/12.2286102
Show Author Affiliations
Santiago S. Silva R., Univ. Nacional de Colombia (Colombia)
Diana L. Giraldo, Univ. Nacional de Colombia (Colombia)
Eduardo Romero, Univ. Nacional de Colombia (Colombia)


Published in SPIE Proceedings Vol. 10572:
13th International Conference on Medical Information Processing and Analysis
Eduardo Romero; Natasha Lepore; Jorge Brieva; Juan David García, Editor(s)

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