Dissimilarity-based detection of schizophrenia

A. Ulaş, R. P W Duin, U. Castellani, M. Loog, M. Bicego, V. Murino, M. Bellani, S. Cerruti, M. Tansella, P. Brambilla

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

Abstract

We propose to approach the detection of patients affected by schizophrenia by means of dissimilarity-based classification techniques applied to brain magnetic resonance images. Instead of working with features directly, pairwise distances between expert delineated regions of interest (ROIs) are considered as representations based on which learning and classification can be performed. Experiments were carried out on a set of 64 patients and 60 controls and several pairwise dissimilarity measurements have been analyzed. We demonstrate that good results are possible and especially significant improvements can be obtained when combining over different ROIs and different distance measures. The lowest error rate obtained is 0.210.

Original languageEnglish
Title of host publicationProceedings - Workshop on Brain Decoding: Pattern Recognition Challenges in Neuroimaging, WBD 2010 - In Conjunction with theInternational Conference on Pattern Recognition, ICPR 2010
Pages32-35
Number of pages4
DOIs
Publication statusPublished - 2010
EventWorkshop on Brain Decoding: Pattern Recognition Challenges in Neuroimaging, WBD 2010 - In Conjunction with the International Conference on Pattern Recognition, ICPR 2010 - Istanbul, Turkey
Duration: Aug 22 2010Aug 22 2010

Other

OtherWorkshop on Brain Decoding: Pattern Recognition Challenges in Neuroimaging, WBD 2010 - In Conjunction with the International Conference on Pattern Recognition, ICPR 2010
Country/TerritoryTurkey
CityIstanbul
Period8/22/108/22/10

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Clinical Neurology

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