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arxiv 1710.05006 v3 pith:NCNWDXTZ submitted 2017-10-13 cs.CV

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)

Noel C. F. Codella , David Gutman , M. Emre Celebi , Brian Helba , Michael A. Marchetti , Stephen W. Dusza , Aadi Kalloo , Konstantinos Liopyris
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Nabin Mishra Harald Kittler Allan Halpern
This is my paper
classification cs.CV
keywords challengeskinanalysisdetectiondevelopmentimaginginternationallesion
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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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.

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