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BCN20000: Dermoscopic Lesions in the Wild
by
Helba, Brian
, Carrera, Cristina
, Barreiro, Alicia
, Vilaplana, Veronica
, Codella, Noel C F
, Halpern, Allan C
, Malvehy, Josep
, Rotemberg, Veronica
, Reiter, Ofer
, Combalia, Marc
, Puig, Susana
in
Algorithms
/ Apertures
/ Cancer
/ Datasets
/ Image classification
/ Lesions
/ Skin cancer
2019
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BCN20000: Dermoscopic Lesions in the Wild
by
Helba, Brian
, Carrera, Cristina
, Barreiro, Alicia
, Vilaplana, Veronica
, Codella, Noel C F
, Halpern, Allan C
, Malvehy, Josep
, Rotemberg, Veronica
, Reiter, Ofer
, Combalia, Marc
, Puig, Susana
in
Algorithms
/ Apertures
/ Cancer
/ Datasets
/ Image classification
/ Lesions
/ Skin cancer
2019
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Do you wish to request the book?
BCN20000: Dermoscopic Lesions in the Wild
by
Helba, Brian
, Carrera, Cristina
, Barreiro, Alicia
, Vilaplana, Veronica
, Codella, Noel C F
, Halpern, Allan C
, Malvehy, Josep
, Rotemberg, Veronica
, Reiter, Ofer
, Combalia, Marc
, Puig, Susana
in
Algorithms
/ Apertures
/ Cancer
/ Datasets
/ Image classification
/ Lesions
/ Skin cancer
2019
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Paper
BCN20000: Dermoscopic Lesions in the Wild
2019
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Overview
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, where they will be asked to train algorithms to classify dermoscopic images of skin cancer automatically.
Publisher
Cornell University Library, arXiv.org
Subject
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