BCN20000: Dermoscopic Lesions in the Wild

Hernández-Pérez, Carlos; Combalia, Marc; Podlipnik, Sebastián; Codella, Noel; Rotemberg, Veronica; Halpern, Allan C.; Reiter, Ofer; Carrera, C.; Barreiro, Alicia; Helba, Brian; Puig, Susana; Vilaplana, Verónica; Malvehy, Josep

doi:10.1038/s41597-024-03387-w

articleScientific DataJun 17, 2024GOLD OA

BCN20000: Dermoscopic Lesions in the Wild

CHCarlos Hernández-Pérez MCMarc Combalia SPSebastián Podlipnik NCNoel Codella VRVeronica Rotemberg

Universitat Politècnica de Catalunya · Hospital Clínic de Barcelona · +4 more institutions

PubMed

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Abstract

Advancements in dermatological artificial intelligence research require high-quality and comprehensive datasets that mirror real-world clinical scenarios. We introduce a collection of 18,946 dermoscopic images spanning from 2010 to 2016, collated at the Hospital Clínic in Barcelona, Spain. The BCN20000 dataset aims to address the problem of unconstrained classification of dermoscopic images of skin cancer, including lesions in hard-to-diagnose locations such as those found in nails and mucosa, large lesions which do not fit in the aperture of the dermoscopy device, and hypo-pigmented lesions. Our dataset covers eight key diagnostic categories in dermoscopy, providing a diverse range of lesions for artificial…

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Topics

Keywords

Artificial intelligence
Computer science
Skin lesion
Class (philosophy)
Data set
Training set
Artificial neural network
Machine learning

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