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)

TLDR

Although the challenge has concluded, its dataset snapshots remain available for ongoing research and development. The article presents the design, implementation, and results of the latest dermoscopic image analysis benchmark challenge, aimed at advancing automated melanoma diagnosis algorithms. The challenge comprised three tasks—lesion segmentation, feature detection, and disease classification. The challenge attracted 593 registrations, 81 pre‑submissions, 46 finalized submissions, and about 50 attendees, establishing it as the largest standardized comparative study in dermoscopic image analysis.

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.