Mapping brains on grids of features for schizophrenia analysis

Alessandro Perina, Denis Peruzzo, Kesa Maria Kesa, Nebojsa Jojic, Vittorio Murino, Mellani Bellani, Paolo Brambilla, Umberto Castellani

Research output: Chapter in Book/Report/Conference proceedingChapter


This paper exploits the embedding provided by the counting grid model and proposes a framework for the classification and the analysis of brain MRI images. Each brain, encoded by a count of local features, is mapped into a window on a grid of feature distributions. Similar sample are mapped in close proximity on the grid and their commonalities in their feature distributions are reflected in the overlap of windows on the grid. Here we exploited these properties to design a novel kernel and a visualization strategy which we applied to the analysis of schizophrenic patients. Experiments report a clear improvement in classification accuracy as compared with similar methods. Moreover, our visualizations are able to highlight brain clusters and to obtain a visual interpretation of the features related to the disease.

Original languageEnglish
Title of host publicationMedical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Number of pages8
Publication statusPublished - 2014

ASJC Scopus subject areas

  • Medicine(all)


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