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%0 Conference Proceedings
%4 sid.inpe.br/sibgrapi/2013/07.12.20.08
%2 sid.inpe.br/sibgrapi/2013/07.12.20.08.40
%T Image Segmentation by Image Foresting Transform with Non-smooth Connectivity Functions
%D 2013
%A Mansilla, Lucy A. C.,
%A Cappabianco, Fábio A. M.,
%A Miranda, Paulo A. V.,
%@affiliation Department of Computer Science, University of São Paulo (USP)
%@affiliation Instituto de Ciência e Tecnologia, Universidade Federal de São Paulo
%@affiliation Department of Computer Science, University of São Paulo (USP)
%E Boyer, Kim,
%E Hirata, Nina,
%E Nedel, Luciana,
%E Silva, Claudio,
%B Conference on Graphics, Patterns and Images, 26 (SIBGRAPI)
%C Arequipa, Peru
%8 Aug. 5-8, 2013
%I IEEE Computer Society
%J Los Alamitos
%S Proceedings
%K graph search algorithms, image foresting transform, non-smooth connectivity functions.
%X In the framework of the Image Foresting Transform (IFT), there is a class of connectivity functions that were vaguely explored, which corresponds to the non-smooth connectivity functions (NSCF). These functions are more adaptive to cope with the problems of field inhomogeneity, which are common in MR images of 3 Tesla. In this work, we investigate the NSCF from the standpoint of theoretical and experimental aspects. We formally classify several non-smooth functions according to a proposed diagram representation. Then, we investigate some theoretical properties for some specific regions of the diagram. Our analysis reveals that many NSCFs are, in fact, the result of a sequence of optimizations, each of them involving a maximal set of elements, in a well-structured way. Our experimental results indicate that substantial improvements can be obtained by NSCFs in the 3D segmentation of MR images of 3 Tesla, when compared to smooth connectivity functions.
%@language en
%3 114732_new.pdf


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