Biomedical Image Analysis Challenges (BIAS) Reporting Guideline
Creators
- 1. Division of Computer Assisted Medical Interventions (CAMI), German Cancer Research Center (DKFZ)
- 2. Centre for Biomedical Image Analysis, Masaryk University
- 3. Physical Sciences, Sunnybrook Research Institute; Department Medical Biophysics, University of Toronto
- 4. Centre for Intelligent Machines, McGill University
- 5. Institute of Information Systems Engineering, Technische Universität (TU) Wien; Complexity Science Hub Vienna, Vienna
- 6. Laboratoire Traitement du Signal et de l'Image (LTSI) -UMR_S 1099, Université de Rennes 1, Inserm
- 7. University of Applied Sciences Western Switzerland (HES-SO); Medical Faculty, University of Geneva
- 8. Institute of Computational Biomedicine, Heidelberg University; Faculty of Medicine, Heidelberg University Hospital; Joint Research Centre for Computational Biomedicine, Rheinisch-Westfälische Technische Hochschule (RWTH) Aachen
- 9. Department of Radiology and Nuclear Medicine, Medical Image Analysis, Radboud University Centre
- 10. Division of Biostatistics, German Cancer Research Center (DKFZ)
- 11. Electrical Engineering, Vanderbilt University, Nashville, Tennessee
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. We present 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.
Files
AppendixAReportingGuideline.pdf
Files
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