Patient classification of fMRI activation maps

James Ford, Hany Farid, Fillia Makedon, Laura A. Flashman, Thomas W. McAllister, Vasilis Megalooikonomou, Andrew J. Saykin

Research output: Contribution to journalConference article

38 Scopus citations


The analysis of brain activations using functional magnetic resonance imaging (fMRI) is an active area of neuropsychological research. Standard techniques for analysis have traditionally focused on finding the most significant areas of brain activation, and have only recently begun to explore the importance of their spatial characteristics. We compare fMRI contrast images and significance maps to training sets of similar maps using the spatial distribution of activation values. We demonstrate that a Fisher linear discriminant (FLD) classifier for either type of map can differentiate patients from controls accurately for Alzheimer's disease, schizophrenia, and mild traumatic brain injury (MTBI).

Original languageEnglish (US)
Pages (from-to)58-65
Number of pages8
JournalLecture Notes in Computer Science
Issue numberPART 2
StatePublished - Dec 1 2003
Externally publishedYes
EventMedical Image Computing and Computer-Assisted Intervention, MICCAI 2003 - 6th International Conference Proceedings - Montreal, Que., Canada
Duration: Nov 15 2003Nov 18 2003

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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    Ford, J., Farid, H., Makedon, F., Flashman, L. A., McAllister, T. W., Megalooikonomou, V., & Saykin, A. J. (2003). Patient classification of fMRI activation maps. Lecture Notes in Computer Science, 2879(PART 2), 58-65.