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Dataset Card for ISIC-2019 RESIZED
Dataset Description
Dataset Summary
The original ISIC 2019 dataset contains 25,331 images of dermoscopic images from nine different diagnostic categories. Published by the The International Skin Imaging Collbaroation, it serves as a challenging image classification dataset where the distribution across classes is heavily skewed towards the first two classes.
The ISIC-2019 RESIZED is a downsampled version of the original dataset, downsampled and archived on HuggingFace for convenience of use. The downsampling was performed by Carlo Metta, and the processing was done by Maciej Zuziak.
Citation Rules
The aggregate 'ISIC_2019: Training' data must be cited as original work:
BCN_20000 Dataset: (c) Department of Dermatology, Hospital Clínic de Barcelona
HAM10000 Dataset: (c) by ViDIR Group, Department of Dermatology, Medical University of Vienna; https://doi.org/10.1038/sdata.2018.161 [Add to Citavi project by DOI]
MSK Dataset: (c) Anonymous; https://arxiv.org/abs/1710.05006; https://arxiv.org/abs/1902.03368
When referencing this dataset in your own manuscripts and publications, please use the following full citations:
[1] Tschandl P., Rosendahl C. & Kittler H. The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions. Sci. Data 5, 180161 doi.10.1038/sdata.2018.161 (2018)
[2] Noel C. F. Codella, David Gutman, M. Emre Celebi, Brian Helba, Michael A. Marchetti, Stephen W. Dusza, Aadi Kalloo, Konstantinos Liopyris, Nabin Mishra, Harald Kittler, Allan Halpern: "Skin Lesion Analysis Toward Melanoma Detection: A Challenge at the 2017 International Symposium on Biomedical Imaging (ISBI), Hosted by the International Skin Imaging Collaboration (ISIC)", 2017; arXiv:1710.05006. [Add to Citavi project by ArXiv ID]
[3] Hernández-Pérez C, Combalia M, Podlipnik S, Codella NC, Rotemberg V, Halpern AC, Reiter O, Carrera C, Barreiro A, Helba B, Puig S, Vilaplana V, Malvehy J. BCN20000: Dermoscopic lesions in the wild. Scientific Data. 2024 Jun 17;11(1):641.
Additionally, if the resampled version is used, please cite this repository.
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