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On the spectral signature of melanoma: a non-parametric classification framework for cancer detection in hyperspectral imaging of melanocytic lesions

Abstract: Early detection and diagnosis is a must in secondary prevention of melanoma and other cancerous lesions of the skin. In this work, we present an online, reservoir-based, non-parametric estimation and classification model that allows for this functionality on pigmented lesions, such that detection thresholding can be tuned to maximize accuracy and/or minimize overall false negative rates. This system has been tested in a dataset consisting of 116 patients and a total of 124 hyperspectral images of nevi, raised nevi and melanomas, detecting up to 100% of the suspicious lesions at the expense of some false positives.

 Autoría: Pardo A., Gutiérrez-Gutiérrez J., Lihacova I., López-Higuera J., Conde O.,

 Fuente: Biomedical Optics Express, 2018, 9(12), 6283-6301

Editorial: The Optical Society

 Fecha de publicación: 01/12/2018

Nº de páginas: 19

Tipo de publicación: Artículo de Revista

 DOI: 10.1364/BOE.9.006283

ISSN: 2156-7085

 Proyecto español: TEC2016-76021-C2-2-R

Url de la publicación: https://doi.org/10.1364/BOE.9.006283