Mr. Rudy Mirko Melli Profile

Rudy Mirko Melli

at Univ degli Studi di Modena e Reggio Emilia

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Proceedings Article | 15 March 2006 Paper

Comparison of color clustering algorithms for segmentation of dermatological images

Rudy Melli, Costantino Grana, Rita Cucchiara

Proceedings Volume 6144, 61443S (2006) https://doi.org/10.1117/12.652061

KEYWORDS: Image segmentation, Skin, Medical imaging, Fuzzy logic, Detection and tracking algorithms, Image processing algorithms and systems, Melanoma, Databases, Shape analysis, Visual analytics

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Automatic segmentation of skin lesions in clinical images is a very challenging task; it is necessary for visual analysis of the edges, shape and colors of the lesions to support the melanoma diagnosis, but, at the same time, it is cumbersome since lesions (both naevi and melanomas) do not have regular shape, uniform color, or univocal structure. Most of the approaches adopt unsupervised color clustering. This works compares the most spread color clustering algorithms, namely median cut, k-means, fuzzy-c means and mean shift applied to a method for automatic border extraction, providing an evaluation of the upper bound in accuracy that can be reached with these approaches. Different tests have been performed to examine the influence of the choice of the parameter settings with respect to the performances of the algorithms. Then a new supervised learning phase is proposed to select the best number of clusters and to segment the lesion automatically. Examples have been carried out in a large database of medical images, manually segmented by dermatologists. From these experiments mean shift was resulted the best technique, in term of sensitivity and specificity. Finally, a qualitative evaluation of the goodness of segmentation has been validated by the human experts too, confirming the results of the quantitative comparison.

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