Paper
27 March 2009 A similarity retrieval method for functional magnetic resonance imaging (fMRI) statistical maps
R. F. Tungaraza, J. Guan, S. Rolfe, I. Atmosukarto, A. Poliakov, N. M. Kleinhans, E. Aylward, J. Ojemann, J. F. Brinkley M.D., L. G. Shapiro
Author Affiliations +
Proceedings Volume 7259, Medical Imaging 2009: Image Processing; 72590E (2009) https://doi.org/10.1117/12.811357
Event: SPIE Medical Imaging, 2009, Lake Buena Vista (Orlando Area), Florida, United States
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.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
R. F. Tungaraza, J. Guan, S. Rolfe, I. Atmosukarto, A. Poliakov, N. M. Kleinhans, E. Aylward, J. Ojemann, J. F. Brinkley M.D., and L. G. Shapiro "A similarity retrieval method for functional magnetic resonance imaging (fMRI) statistical maps", Proc. SPIE 7259, Medical Imaging 2009: Image Processing, 72590E (27 March 2009); https://doi.org/10.1117/12.811357
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Cited by 3 scholarly publications.
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KEYWORDS
Functional magnetic resonance imaging

Brain

3D modeling

Brain mapping

3D image processing

Databases

Feature extraction

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