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arXiv 1910.04071cs.CVcs.CYeess.IV
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BIAS：透明报告生物医学图像分析挑战

BIAS: Transparent reporting of biomedical image analysis challenges

German Cancer Research Center (DKFZ)（德国癌症研究中心）；Masaryk University（马萨里克大学）；Sunnybrook Research Institute（桑尼布鲁克研究所）；University of Geneva（日内瓦大学）；Complexity Science Hub Vienna（维也纳复杂性科学中心）；Université de Rennes 1（雷恩第一大学）；Inserm（法国国家健康与医学研究院）；Radboud University（拉德堡德大学）；Heidelberg University（海德堡大学）；University of Toronto（多伦多大学）
Lena Maier-Hein, Annika Reinke, Michal Kozubek, Anne L. Martel, Tal Arbel, Matthias Eisenmann, Allan Hanbuary, Pierre Jannin, Henning Müller, Sinan Onogur, Juli… 展开作者

Lena Maier-Hein, Annika Reinke, Michal Kozubek, Anne L. Martel, Tal Arbel, Matthias Eisenmann, Allan Hanbuary, Pierre Jannin, Henning Müller, Sinan Onogur, Julio Saez-Rodriguez, Bram van Ginneken, Annette Kopp-Schneider, Bennett Landman

备注：
2 Appendices - Appendix A: BIAS reporting guideline for biomedical image analysis challenges, Appendix B: Glossary; 2 Supplements - Suppl 1: Form for summarizing information on challenge organization, Suppl 2: Structured description of a challenge design
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摘要：

每年组织的生物医学图像分析挑战赛的数量正在稳步增加。这些国际竞赛的目的是在通用数据集上对算法进行基准测试，通常是为了确定解决给定问题的最佳方法。然而，最近的研究表明，与挑战报告相关的常见做法不允许对结果进行充分的解释和再现。为了解决挑战的影响和质量（控制）之间的差异，生物医学图像分析系统（BIAS）倡议制定了一套挑战报告建议。BIAS声明旨在提高生物医学图像分析挑战报告的透明度，无论评估的应用领域、图像模式或任务类别如何。本文介绍了BIAS声明是如何制定的，并提出了一个清单，鼓励生物医学图像分析挑战的作者在提交一篇关于挑战的论文时将其纳入审查。检查表的目的是通过明确相关信息来规范和促进审查过程，并提高挑战结果的可解释性和重现性。

英文摘要：

The number of biomedical image analysis challenges organized per year is steadily increasing. These international competitions have the purpose of benchmarking algorithms on common data sets, typically to identify the best method for a given problem. Recent research, however, revealed that common practice related to challenge reporting does not allow for adequate interpretation and reproducibility of results. To address the discrepancy between the impact of challenges and the quality (control), the Biomedical I mage Analysis ChallengeS (BIAS) initiative developed a set of recommendations for the reporting of challenges. The BIAS statement aims to improve the transparency of the reporting of a biomedical image analysis challenge regardless of field of application, image modality or task category assessed. This article describes how the BIAS statement was developed and presents a checklist which authors of biomedical image analysis challenges are encouraged to include in their submission when giving a paper on a challenge into review. The purpose of the checklist is to standardize and facilitate the review process and raise interpretability and reproducibility of challenge results by making relevant information explicit.

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