A Similarity Retrieval Tool for Functional Magnetic Resonance Imaging Statistical Maps

Tungaraza, Rosalia and Guan, Jinyan and Shapiro, Linda and Brinkley, James F and Ojemann, Jeffrey and Franklin, Joshua (2013) A Similarity Retrieval Tool for Functional Magnetic Resonance Imaging Statistical Maps. International Journal of Biomedical Data Mining, 2. pp. 1-12. ISSN 2090-4916

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Abstract

Objective. We propose a method for retrieving similar func- tional magnetic resonance imaging (fMRI) statistical images given a query fMRI statistical image. Method. Our method thresholds the vox- els within those images and extracts spatially distinct regions from the voxels that remain. Each region is defined by a feature vector that contains the region centroid, the region area, the average activation value for all the voxels within that region, the variance of those acti- vation values, the average distance of each voxel within that region to the region’s centroid, and the variance of the voxel’s distance to the region’s centroid. The similarity between two images is obtained by the summed minimum distance (SMD) of their constituent feature vectors. Results and conclusion. Our method is sensitive to similarities in brain activation patterns from members of the same data set. Using a subset of the features such as the centroid location and the average activation value (individually or in combination), maximized the sensitivity of our method. We also identified the similarity structure of the entire data set using those two features and the SMD.

Item Type: Article
Subjects: All Projects > Brain Mapping
Divisions: University of Washington > Department of Biological Structure
University of Washington > Department of Biomedical Informatics and Medical Education
University of Washington > Department of Computer Science and Engineering
Depositing User: Jim Brinkley
Date Deposited: 23 Jun 2018 00:48
Last Modified: 09 May 2019 23:33
URI: http://sigpubs.si.washington.edu/id/eprint/290

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