Medical Image Segmentation with Multifractals

Abstract : Multifractal analysis provides a different way to process images. Instead of assuming smoothness properties, one characterizes the different elements of an image (e.g. edges, textures) by their regularity. This regularity is measured both in a local way, through the Hölder exponent, and in a global one, through the multifractal spectrum. Such an approach is particularly fitted for medical images, which are by their very nature mostly irregular. We provide examples of applications of this new paradigm to various cases.
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Chapitre d'ouvrage
Edwin Diday and Yves Lechevallier and Martin Schader and Patrice Bertrand and Bernard Burtschy. New Approaches in Classification and Data Analysis, Springer, 1994, Studies in Classification, Data Analysis and Knowledge Organization, 978-3540584254
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https://hal.inria.fr/inria-00613970
Contributeur : Lisandro Fermin <>
Soumis le : lundi 8 août 2011 - 12:31:51
Dernière modification le : vendredi 25 mai 2018 - 12:02:05

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  • HAL Id : inria-00613970, version 1

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Jacques Lévy-Vehel. Medical Image Segmentation with Multifractals. Edwin Diday and Yves Lechevallier and Martin Schader and Patrice Bertrand and Bernard Burtschy. New Approaches in Classification and Data Analysis, Springer, 1994, Studies in Classification, Data Analysis and Knowledge Organization, 978-3540584254. 〈inria-00613970〉

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