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.

本篇论文总结了 BCN20000 数据集，该集包含来自巴塞罗那医学中心在 2010 年至 2016 年期间拍摄的 19424 张皮肤镜检影像，旨在研究皮肤癌的非受限分类问题，包括在难以诊断的部位（指甲和黏膜），不适合镜检设备孔径的大型病变和低色素病变。BCN20000 将提供给 ISIC Challenge 2019 的参与者使用，参与者需要训练算法自动分类皮肤癌镜检影像。