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BCN20000: Dermoscopic Lesions in the Wild

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arxiv 1908.02288 v2 pith:FC3GSNAP submitted 2019-08-06 eess.IV cs.CV

Marc Combalia , Noel C. F. Codella , Veronica Rotemberg , Brian Helba , Veronica Vilaplana , Ofer Reiter , Cristina Carrera , Alicia Barreiro
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Allan C. Halpern Susana Puig Josep Malvehy
This is my paper · ORCID
classification eess.IVcs.CV
keywords lesionsdermoscopicbcn20000imagesskincancerdatasetwill
verification ladder T0 review T1 audit T2 compute T3 formal
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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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Cited by 6 Pith papers

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