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PAD-UFES-20: A skin lesion dataset composed of patient data and clinical images collected from smartphones

2020; Elsevier BV; Volume: 32; Linguagem: Inglês

10.1016/j.dib.2020.106221

2352-3409

André G. C. Pacheco, Gustavo Ribeiro Lima, Amanda S. Salomão, Breno Krohling, Igor Peixoto Biral, Gabriel G. de Angelo, Fábio C. R. Alves, José G. M. Esgario, Alana C. Simora, Pedro B. C. Castro, Felipe B. Rodrigues, Patricia H. L. Frasson, Renato A. Krohling, Helder Knidel, Maria C. S. Santos, Rachel Bertolani do Espírito Santo, Telma L. S. G. Macedo, Tania R. P. Canuto, Luíz F. S. de Barros,

Cutaneous lymphoproliferative disorders research

Over the past few years, different Computer-Aided Diagnosis (CAD) systems have been proposed to tackle skin lesion analysis. Most of these systems work only for dermoscopy images since there is a strong lack of public clinical images archive available to evaluate the aforementioned CAD systems. To fill this gap, we release a skin lesion benchmark composed of clinical images collected from smartphone devices and a set of patient clinical data containing up to 21 features. The dataset consists of 1373 patients, 1641 skin lesions, and 2298 images for six different diagnostics: three skin diseases and three skin cancers. In total, 58.4% of the skin lesions are biopsy-proven, including 100% of the skin cancers. By releasing this benchmark, we aim to support future research and the development of new tools to assist clinicians to detect skin cancer.