A new shape diffusion descriptor for brain classification

Authors:
Umberto Castellani;Pasquale Mirtuono;Vittorio Murino;Marcella Bellani;Gianluca Rambaldelli;Michele Tansella;Paolo Brambilla
Affiliations:
VIPS lab, University of Verona, Italy;VIPS lab, University of Verona, Italy;VIPS lab, University of Verona, Italy and Istituto Italiano di Tecnologia, Italy;Department of Public Health and Community Medicine, Inter-University Center for Behavioural Neurosciences, University of Verona, Italy;Department of Public Health and Community Medicine, Inter-University Center for Behavioural Neurosciences, University of Verona, Italy;Department of Public Health and Community Medicine, Inter-University Center for Behavioural Neurosciences, University of Verona, Italy;Department of Experimental Clinical Medical Sciences, Inter-University, Center for Behavioral Neurosciences, University of Udine, Italy and Scientific Institute IRCCS "E. Medea", Udine, Italy
Venue:
MICCAI'11 Proceedings of the 14th international conference on Medical image computing and computer-assisted intervention - Volume Part II
Year:
2011

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Abstract

In this paper, we exploit spectral shape analysis techniques to detect brain morphological abnormalities. We propose a new shape descriptor able to encode morphometric properties of a brain image or region using diffusion geometry techniques based on the local Heat Kernel. Using this approach, it is possible to design a versatile signature, employed in this case to classify between normal subjects and patients affected by schizophrenia. Several diffusion strategies are assessed to verify the robustness of the proposed descriptor under different deformation variations. A dataset consisting of MRI scans from 30 patients and 30 control subjects is utilized to test the proposed approach, which achieves promising classification accuracies, up to 83.33%. This constitutes a drastic improvement in comparison with other shape description techniques.