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BIAS: Transparent reporting of biomedical image analysis challenges
L. Maier-Hein, A. Reinke, M. Kozubek, AL. Martel, T. Arbel, M. Eisenmann, A. Hanbury, P. Jannin, H. Müller, S. Onogur, J. Saez-Rodriguez, B. van Ginneken, A. Kopp-Schneider, BA. Landman
Language English Country Netherlands
Document type Journal Article, Research Support, N.I.H., Extramural, Research Support, Non-U.S. Gov't, Research Support, U.S. Gov't, Non-P.H.S.
Grant support
R01 EB017230
NIBIB NIH HHS - United States
- MeSH
- Biomedical Research * MeSH
- Checklist * MeSH
- Humans MeSH
- Prognosis MeSH
- Reproducibility of Results MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Research Support, N.I.H., Extramural MeSH
- Research Support, U.S. Gov't, Non-P.H.S. MeSH
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.
Centre for Biomedical Image Analysis Masaryk University Botanická 68a Brno 60200 Czech Republic
Complexity Science Hub Vienna Josefstädter Straße 39 Vienna 1080 Austria
Division of Computer Assisted Medical Interventions Im Neuenheimer Feld 223 Heidelberg 69120 Germany
Electrical Engineering Vanderbilt University Nashville Tennessee TN 37235 1679 USA
Heidelberg University Hospital Im Neuenheimer Feld 267 Heidelberg 69120 Germany
Medical Faculty University of Geneva Rue Gabrielle Perret Gentil 4 Geneva 1211 Switzerland
University of Applied Sciences Western Switzerland Rue du Technopole 3 Sierre 3960 Switzerland
References provided by Crossref.org
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