计算机科学
皮肤癌
水准点(测量)
皮肤损伤
特征(语言学)
分割
排名(信息检索)
医学影像学
人工智能
医学物理学
医学
数据科学
皮肤病科
癌症
地图学
地理
哲学
内科学
语言学
作者
Noel Codella,David Gutman,M. Emre Celebi,Brian Helba,Michael A. Marchetti,Stephen W. Dusza,Aadi Kalloo,Konstantinos Liopyris,Nabin K. Mishra,Harald Kittler,Allan C. Halpern
出处
期刊:
日期:2018-04-01
卷期号:: 168-172
被引量:1827
标识
DOI:10.1109/isbi.2018.8363547
摘要
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.
科研通智能强力驱动
Strongly Powered by AbleSci AI