Automated skin lesion segmentation with kernel density estimation

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URI: http://hdl.handle.net/10902/13291
ISBN: 978-1-5106-1280-8
ISBN: 978-1-5106-1281-5
ISSN: 0277-786X
ISSN: 1996-756X
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Autoría
Pardo Franco, ArturoAutoridad Unican; Real Peña, EusebioAutoridad Unican; Fernández Barreras, Gaspar; Madruga Saavedra, Francisco JavierAutoridad Unican; López Higuera, José MiguelAutoridad Unican; Conde Portilla, Olga MaríaAutoridad Unican
Fecha
2017
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Copyright 2017 Society of Photo-Optical Instrumentation Engineers and Optical Society of America. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
Publicado en
A. Pardo, E. Real, G. Fernandez-Barreras, F. Madruga, J. López-Higuera, and O. Conde, "Automated skin lesion segmentation with kernel density estimation," in European Conference on Biomedical Optics: Clinical and Preclinical Optical Diagnostics, J. Quincy Brown and Ton G. van Leeuwen, eds., Vol. 10411 of Proceedings of SPIE-OSA Biomedical Optics, 104110P, (2017)
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SPIE Society of Photo-Optical Instrumentation Engineers-
The Optical Society (OSA)
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Palabras clave
Kernel density estimation
Skin lesion
Melanoma
Segmentation
Resumen/Abstract
Skin lesion segmentation is a complex step for dermoscopy pathological diagnosis. Kernel density estimation is proposed as a segmentation technique based on the statistic distribution of color intensities in the lesion and non-lesion regions.
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