生物医学图像分析竞赛排名应谨慎解读的原因
计算机视觉与模式识别
2019-09-19 v2
摘要
国际挑战赛已成为验证生物医学图像分析方法的标准。鉴于其科学影响，令人惊讶的是尚未对与挑战赛组织相关的常见实践进行批判性分析。在本文中，我们对迄今为止进行的生物医学图像分析挑战赛进行了全面分析。我们展示了挑战赛的重要性，并表明缺乏质量控制会带来严重后果。首先，由于通常仅提供一小部分相关信息，结果的可重复性和解释常常受到阻碍。其次，算法的排名通常对若干变量不具稳健性，例如用于验证的测试数据、所采用的排名方案以及制作参考标注的观察者。为克服这些问题，我们推荐最佳实践指南并定义了未来需解决的开放研究问题。
引用
@article{arxiv.1806.02051,
title = {Why rankings of biomedical image analysis competitions should be interpreted with care},
author = {Lena Maier-Hein and Matthias Eisenmann and Annika Reinke and Sinan Onogur and Marko Stankovic and Patrick Scholz and Tal Arbel and Hrvoje Bogunovic and Andrew P. Bradley and Aaron Carass and Carolin Feldmann and Alejandro F. Frangi and Peter M. Full and Bram van Ginneken and Allan Hanbury and Katrin Honauer and Michal Kozubek and Bennett A. Landman and Keno März and Oskar Maier and Klaus Maier-Hein and Bjoern H. Menze and Henning Müller and Peter F. Neher and Wiro Niessen and Nasir Rajpoot and Gregory C. Sharp and Korsuk Sirinukunwattana and Stefanie Speidel and Christian Stock and Danail Stoyanov and Abdel Aziz Taha and Fons van der Sommen and Ching-Wei Wang and Marc-André Weber and Guoyan Zheng and Pierre Jannin and Annette Kopp-Schneider},
journal= {arXiv preprint arXiv:1806.02051},
year = {2019}
}
备注
Article published in Nature Communications: https://rdcu.be/bRmNr