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.
翻译:本篇文章总结了BCN20000数据集,该数据集由2010年至2016年巴塞罗那Cl\'inic医院设施中采集的19424张皮肤损伤脱温镜像组成,我们打算利用该数据集研究皮肤癌脱热镜像不受限制分类的问题,包括难以诊断地点(针叶和肌肉)发现的损伤、与脱温器孔径不相容的大型损伤以及分泌损伤。BCN20000将提供给国际标准行业分类挑战2019的参与者,请他们在那里培训算法,对皮肤癌脱热镜像进行自动分类。