Skin Lesion Analysis Toward Melanoma Detection: A Challenge at the 2017\n International Symposium on Biomedical Imaging (ISBI), Hosted by the\n International Skin Imaging Collaboration (ISIC)

2017/10/13 by Noel Codella, Codella, Noel C. F., David A. Gutman +19 · 54 citations
Medicine · #Computer Vision and Pattern Recognition (cs.CV) #Cutaneous Melanoma Detection and Management #FOS: Computer and information sciences #Skin Protection and Aging

paper · pdf · doi:10.48550/arxiv.1710.05006

openalex publication_date 2017/10/13 · openalex created_date 2022/10/01 · openalex updated_date 2026/07/28

Abstract

This article describes the design, implementation, and results of the latest\ninstallment of the dermoscopic image analysis benchmark challenge. The goal is\nto support research and development of algorithms for automated diagnosis of\nmelanoma, the most lethal skin cancer. The challenge was divided into 3 tasks:\nlesion segmentation, feature detection, and disease classification.\nParticipation involved 593 registrations, 81 pre-submissions, 46 finalized\nsubmissions (including a 4-page manuscript), and approximately 50 attendees,\nmaking this the largest standardized and comparative study in this field to\ndate. While the official challenge duration and ranking of participants has\nconcluded, the dataset snapshots remain available for further research and\ndevelopment.\n

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