Publication details

BIAS: Transparent reporting of biomedical image analysis challenges

Authors

MAIER-HEIN Lena REINKE Annika KOZUBEK Michal MARTEL Anne L. ARBEL Tal EISENMANN Matthias HANBURY Allan JANNIN Pierre MÜLLER Henning ONOGUR Sinan SAEZ-RODRIGUEZ Julio VAN GINNEKEN Bram KOPP-SCHNEIDER Annette LANDMAN Bennett A.

Year of publication 2020
Type Article in Periodical
Magazine / Source Medical Image Analysis
MU Faculty or unit

Faculty of Informatics

Citation
Web https://doi.org/10.1016/j.media.2020.101796
Doi http://dx.doi.org/10.1016/j.media.2020.101796
Keywords Biomedical challenges;Good scientific practice;Biomedical image analysis;Guideline
Attached files
Description 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 Image 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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