BCN20000: Dermoscopic Lesions in the Wild

Marc Combalia, Noel Codella, Veronica Rotemberg, Brian Helba, Verónica Vilaplana, Ofer Reiter, C. Carrera, Alicia Barreiro, Allan C. Halpern, Susana Puig,

UPCommons institutional repository (Universitat Politècnica de Catalunya) · 2019 · 294 citations · 7 references

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

References

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