BCN20000: dermoscopic lesions in the wild

Combalia, Marc; Codella, Noel C. F.; Rotemberg, Veronica; Vilaplana Besler, Verónica

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Combalia, Marc

Codella, Noel C. F.

Rotemberg, Veronica

Vilaplana Besler, Verónica

Document typeResearch report

Defense date2019

Rights accessOpen Access

All rights reserved. This work is protected by the corresponding intellectual and industrial property rights. Without prejudice to any existing legal exemptions, reproduction, distribution, public communication or transformation of this work are prohibited without permission of the copyright holder

Abstract

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 Clínic 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 [8], where they will be asked to train algorithms to classify dermoscopic images of skin cancer automatically.

CitationCombalia, M. [et al.]. "BCN20000: dermoscopic lesions in the wild". 2019.

URIhttp://hdl.handle.net/2117/175069

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