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Proceedings Paper

A similarity retrieval method for functional magnetic resonance imaging (fMRI) statistical maps
Author(s): R. F. Tungaraza; J. Guan; S. Rolfe; I. Atmosukarto; A. Poliakov; N. M. Kleinhans; E. Aylward; J. Ojemann; J. F. Brinkley; L. G. Shapiro
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Paper Abstract

We propose a method for retrieving similar fMRI statistical images given a query fMRI statistical image. Our method thresholds the voxels 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 activation 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 of their constituent feature vectors. Results on a dataset of fMRI statistical images from experiments involving distinct cognitive tasks are shown.

Paper Details

Date Published: 27 March 2009
PDF: 12 pages
Proc. SPIE 7259, Medical Imaging 2009: Image Processing, 72590E (27 March 2009); doi: 10.1117/12.811357
Show Author Affiliations
R. F. Tungaraza, Univ. of Washington (United States)
J. Guan, Univ. of Washington (United States)
S. Rolfe, Univ. of Washington (United States)
I. Atmosukarto, Univ. of Washington (United States)
A. Poliakov, Univ. of Washington (United States)
N. M. Kleinhans, Univ. of Washington (United States)
E. Aylward, Univ. of Washington (United States)
J. Ojemann, Seattle Children's Hospital (United States)
J. F. Brinkley, Univ. of Washington (United States)
L. G. Shapiro, Univ. of Washington (United States)


Published in SPIE Proceedings Vol. 7259:
Medical Imaging 2009: Image Processing
Josien P. W. Pluim; Benoit M. Dawant, Editor(s)

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