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Updated: Apr 19, 2026

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Published on: June 26, 2013
Statistical significance in the selection of the regions of interest for Parkinson brain image processing
Pablo Padilla1, Javier Ramírez1, Juan Manuel Górriz1
1University of Granada - CITIC, Periodista Daniel Saucedo Aranda S/N, 18071 Granada, Spain.
Abstract:
This paper presents the analysis of the statistical significance in the selection of the ROI for the discriminant analysis of brain images to identify Parkinson patients or subjects without any pathology. The particular features and brain functional patterns of the Parkinson's disease cause that there are regions that conveniently reveal the presence of the pathology, in this case mainly the striatum region. The selection of the brain mask makes incidence in two main aspects: the selection of the region of interest (striatum and surrounding area) for the analysis, but also the selection of the region without significance, which is the reference area for the intensity normalization, previous to the analysis. This work studies the statistical significance in the selection of ROIs in 3D brain images for Parkinson, depending on the objective to be achieved in the posterior analysis process.
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