Task 3: Lesion Diagnosis: Training

Training data for Task 3: Lesion Diagnosis may be downloaded from the challenge submission site.

The training data consists of 10015 images and 1 ground truth response CSV file (containing 1 header row and 10015 corresponding response rows).

Supplemental information is also available for the training data, which may be helpful when splitting the data for internal training / evaluation processes. Full information is available here.

Please cite the use of this data as:

Our data was extracted from the “ISIC 2018: Skin Lesion Analysis Towards Melanoma Detection” grand challenge datasets [1][2].

 

[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.

Note: All data for this task is provided under the terms of the Creative Commons Attribution-NonCommercial (CC BY-NC) 4.0 license. If you are unable to accept the terms of this license, do not download or use this data.