40 Einstein St., Ramat Aviv Mall Tower, 3rd floor, Tel Aviv


A PREPRINT Marc Combalia1, Noel C. F. Codella2, Veronica Rotemberg3, Brian Helba4, Veronica Vilaplana5, Ofer Reiter3, Cristina Carrera1, Alicia Barreiro1, Allan C. Halpern3, Susana Puig1, and Josep Malvehy1   ABSTRACT 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 Clínic 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 [8], where they will be asked to train algorithms to classify dermoscopic images of skin cancer automatically
Share the Post:

Latest Researches

In need of treatment? guidance?

Give us a call or fill in your details and we will get back to you

זקוקים לטיפול? צריכים הכוונה?

מלאו פרטים או התקשרו. ואחזור אליכם בהקדם

Skip to content