%0 Generic %1 codella2017lesion %A Codella, Noel C. F. %A Gutman, David %A Celebi, M. Emre %A Helba, Brian %A Marchetti, Michael A. %A Dusza, Stephen W. %A Kalloo, Aadi %A Liopyris, Konstantinos %A Mishra, Nabin %A Kittler, Harald %A Halpern, Allan %D 2017 %K Dermatology %T 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) %U http://arxiv.org/abs/1710.05006 %X This article describes the design, implementation, and results of the latest installment of the dermoscopic image analysis benchmark challenge. The goal is to support research and development of algorithms for automated diagnosis of melanoma, the most lethal skin cancer. The challenge was divided into 3 tasks: lesion segmentation, feature detection, and disease classification. Participation involved 593 registrations, 81 pre-submissions, 46 finalized submissions (including a 4-page manuscript), and approximately 50 attendees, making this the largest standardized and comparative study in this field to date. While the official challenge duration and ranking of participants has concluded, the dataset snapshots remain available for further research and development.

@misc{codella2017lesion, abstract = {This article describes the design, implementation, and results of the latest installment of the dermoscopic image analysis benchmark challenge. The goal is to support research and development of algorithms for automated diagnosis of melanoma, the most lethal skin cancer. The challenge was divided into 3 tasks: lesion segmentation, feature detection, and disease classification. Participation involved 593 registrations, 81 pre-submissions, 46 finalized submissions (including a 4-page manuscript), and approximately 50 attendees, making this the largest standardized and comparative study in this field to date. While the official challenge duration and ranking of participants has concluded, the dataset snapshots remain available for further research and development.}, added-at = {2018-09-04T09:17:49.000+0200}, author = {Codella, Noel C. F. and Gutman, David and Celebi, M. Emre and Helba, Brian and Marchetti, Michael A. and Dusza, Stephen W. and Kalloo, Aadi and Liopyris, Konstantinos and Mishra, Nabin and Kittler, Harald and Halpern, Allan}, biburl = {https://www.bibsonomy.org/bibtex/28c67e6763fd333814ba080043df84327/dschlessinger}, description = {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)}, interhash = {08d50a87d5c1332b00b23c7494d24506}, intrahash = {8c67e6763fd333814ba080043df84327}, keywords = {Dermatology}, note = {cite arxiv:1710.05006}, timestamp = {2018-09-04T09:17:49.000+0200}, title = {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)}, url = {http://arxiv.org/abs/1710.05006}, year = 2017 }