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Proceedings Paper

Border preserving skin lesion segmentation
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Paper Abstract

Melanoma is a fatal cancer with a growing incident rate. However it could be cured if diagnosed in early stages. The first step in detecting melanoma is the separation of skin lesion from healthy skin. There are particular features associated with a malignant lesion whose successful detection relies upon accurately extracted borders. We propose a two step approach. First, we apply K-means clustering method (to 3D RGB space) that extracts relatively accurate borders. In the second step we perform an extra refining step for detecting the fading area around some lesions as accurately as possible. Our method has a number of novelties. Firstly as the clustering method is directly applied to the 3D color space, we do not overlook the dependencies between different color channels. In addition, it is capable of extracting fine lesion borders up to pixel level in spite of the difficulties associated with fading areas around the lesion. Performing clustering in different color spaces reveals that 3D RGB color space is preferred. The application of the proposed algorithm to an extensive data-base of skin lesions shows that its performance is superior to that of existing methods both in terms of accuracy and computational complexity.

Paper Details

Date Published: 17 March 2008
PDF: 9 pages
Proc. SPIE 6915, Medical Imaging 2008: Computer-Aided Diagnosis, 69153A (17 March 2008); doi: 10.1117/12.770574
Show Author Affiliations
Mostafa Kamali, Institute for Studies in Theoretical Physics and Mathematics (Iran)
Golnoosh Samei, Institute for Studies in Theoretical Physics and Mathematics (Iran)


Published in SPIE Proceedings Vol. 6915:
Medical Imaging 2008: Computer-Aided Diagnosis
Maryellen L. Giger; Nico Karssemeijer, Editor(s)

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