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

Pardo Franco, Arturo; Gutiérrez Gutiérrez, José Alberto; Lihacova, Ilze; López Higuera, José Miguel; Conde Portilla, Olga María

doi:10.1364/BOE.9.006283

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Identificadores

URI: http://hdl.handle.net/10902/15658

DOI: 10.1364/BOE.9.006283

ISSN: 2156-7085

Fecha

2018-12-01

Derechos

© 2018 Optica Publishing Group under the terms of the Open Access Publishing Agreement. Users may use, reuse, and build upon the article, or use the article for text or data mining, so long as such uses are for non-commercial purposes and appropriate attribution is maintained. All other rights are reserved.

Publicado en

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

Editorial

The Optical Society

Enlace a la publicación

https://doi.org/10.1364/BOE.9.006283

Resumen/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.