arxiv:1908.02288

BCN20000: Dermoscopic Lesions in the Wild

Published on Aug 6, 2019

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Abstract

The BCN20000 dataset, consisting of 19,424 dermoscopic images, is utilized to study the unconstrained classification of skin cancer images, especially challenging cases, for use in the ISIC Challenge 2019.

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This article summarizes the BCN20000 dataset, composed of 19424 dermoscopic images of skin lesions captured from 2010 to 2016 in the facilities of the Hospital Cl\'inic in Barcelona. With this dataset, we aim to study the problem of unconstrained classification of dermoscopic images of skin cancer, including lesions found in hard-to-diagnose locations (nails and mucosa), large lesions which do not fit in the aperture of the dermoscopy device, and hypo-pigmented lesions. The BCN20000 will be provided to the participants of the ISIC Challenge 2019, where they will be asked to train algorithms to classify dermoscopic images of skin cancer automatically.

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