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, L. G. Shapiro

Research output: Chapter in Book/Report/Conference proceedingConference contribution


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.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2009 - Image Processing
StatePublished - Dec 15 2009
Externally publishedYes
EventMedical Imaging 2009 - Image Processing - Lake Buena Vista, FL, United States
Duration: Feb 8 2009Feb 10 2009

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
ISSN (Print)1605-7422


OtherMedical Imaging 2009 - Image Processing
Country/TerritoryUnited States
CityLake Buena Vista, FL


  • Functional imaging
  • Pattern recognition

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Atomic and Molecular Physics, and Optics
  • Radiology Nuclear Medicine and imaging


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