Data in Brief (Oct 2020)
PAD-UFES-20: A skin lesion dataset composed of patient data and clinical images collected from smartphones
- Andre G.C. Pacheco,
- Gustavo R. Lima,
- Amanda S. Salomão,
- Breno Krohling,
- Igor P. Biral,
- Gabriel G. de Angelo,
- Fábio C.R. Alves Jr,
- 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 B. do Espírito Santo,
- Telma L.S.G. Macedo,
- Tania R.P. Canuto,
- Luíz F.S. de Barros
Affiliations
- Andre G.C. Pacheco
- Corresponding author at: Graduate Program in Computer Science, Federal University of Espírito Santo, Vitória, Brazil.; Graduate Program in Computer Science, Federal University of Espírito Santo, Vitória, Brazil; Nature Inspired Computing Laboratory, Federal University of Espírito Santo, Vitória, Brazil
- Gustavo R. Lima
- Dermatological and Surgical Assistance Program (PAD), Federal University of Espírito Santo, Vitória, Brazil; Faculty of Medicine, Federal University of Espírito Santo, Vitória, Brazil
- Amanda S. Salomão
- Dermatological and Surgical Assistance Program (PAD), Federal University of Espírito Santo, Vitória, Brazil; Faculty of Medicine, Federal University of Espírito Santo, Vitória, Brazil
- Breno Krohling
- Nature Inspired Computing Laboratory, Federal University of Espírito Santo, Vitória, Brazil
- Igor P. Biral
- Dermatological and Surgical Assistance Program (PAD), Federal University of Espírito Santo, Vitória, Brazil; Faculty of Medicine, Federal University of Espírito Santo, Vitória, Brazil
- Gabriel G. de Angelo
- Nature Inspired Computing Laboratory, Federal University of Espírito Santo, Vitória, Brazil
- Fábio C.R. Alves Jr
- Dermatological and Surgical Assistance Program (PAD), Federal University of Espírito Santo, Vitória, Brazil; Faculty of Medicine, Federal University of Espírito Santo, Vitória, Brazil
- José G.M. Esgario
- Graduate Program in Computer Science, Federal University of Espírito Santo, Vitória, Brazil; Nature Inspired Computing Laboratory, Federal University of Espírito Santo, Vitória, Brazil
- Alana C. Simora
- Dermatological and Surgical Assistance Program (PAD), Federal University of Espírito Santo, Vitória, Brazil; Faculty of Medicine, Federal University of Espírito Santo, Vitória, Brazil
- Pedro B.C. Castro
- Nature Inspired Computing Laboratory, Federal University of Espírito Santo, Vitória, Brazil
- Felipe B. Rodrigues
- Nature Inspired Computing Laboratory, Federal University of Espírito Santo, Vitória, Brazil
- Patricia H.L. Frasson
- Department of Specialized Medicine, Federal University of Espírito Santo, Vitória, Brazil; Dermatological and Surgical Assistance Program (PAD), Federal University of Espírito Santo, Vitória, Brazil
- Renato A. Krohling
- Graduate Program in Computer Science, Federal University of Espírito Santo, Vitória, Brazil; Nature Inspired Computing Laboratory, Federal University of Espírito Santo, Vitória, Brazil; Production Engineering Department, Federal University of Espírito Santo, Vitória, Brazil
- Helder Knidel
- Nature Inspired Computing Laboratory, Federal University of Espírito Santo, Vitória, Brazil
- Maria C.S. Santos
- Pathological Anatomy Unit of the University Hospital Cassiano Antônio Moraes (HUCAM), Federal University of Espírito Santo, Vitória, Brazil
- Rachel B. do Espírito Santo
- Secretary of Health of the Espírito Santo state, Governor of Espírito Santo state, Vitória, Brazil; Dermatological and Surgical Assistance Program (PAD), Federal University of Espírito Santo, Vitória, Brazil
- Telma L.S.G. Macedo
- Secretary of Health of the Espírito Santo state, Governor of Espírito Santo state, Vitória, Brazil; Dermatological and Surgical Assistance Program (PAD), Federal University of Espírito Santo, Vitória, Brazil
- Tania R.P. Canuto
- Secretary of Health of the Espírito Santo state, Governor of Espírito Santo state, Vitória, Brazil; Dermatological and Surgical Assistance Program (PAD), Federal University of Espírito Santo, Vitória, Brazil
- Luíz F.S. de Barros
- Dermatological and Surgical Assistance Program (PAD), Federal University of Espírito Santo, Vitória, Brazil
- Journal volume & issue
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Vol. 32
p. 106221
Abstract
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.
