Iterative fuzzy clustering for detecting regions of interesting skin lesions, Atti del Workshop su Intelligenza Artificiale, Visione e Pattern Recognition (in conjunction with AI*IA 2001): 3138 (2001)
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BibTeX
@MISC{Cucchiara01iterativefuzzy,
author = {Rita Cucchiara and Costantino Grana and Massimo Piccardi},
title = {Iterative fuzzy clustering for detecting regions of interesting skin lesions, Atti del Workshop su Intelligenza Artificiale, Visione e Pattern Recognition (in conjunction with AI*IA 2001): 3138},
year = {2001}
}
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Abstract
ABSTRACT Image analysis tools are spreading in dermatology since the introduction of dermoscopy (epiluminescence microscopy), in the effort of algorithmically reproducing clinical evaluations. Color-based region segmentation of skin lesions is one of the key steps for correctly collecting statistics that can help clinicians in their diagnosis. Nevertheless, an efficient and accurate region segmentation algorithm has not been proposed in the literature yet. This work proposes an iterative fuzzy c-means clustering algorithm based on PCA with the KarhunenLoève transform of the color space. A topological tree is provided to store the mutual inclusions of the regions and then used to summarize the structural properties of the skin lesion. Preliminary experimental results are presented and discussed.
