MAIER-HEIN, Lena, Annika REINKE, Michal KOZUBEK, Anne L. MARTEL, Tal ARBEL, Matthias EISENMANN, Allan HANBURY, Pierre JANNIN, Henning MÜLLER, Sinan ONOGUR, Julio SAEZ-RODRIGUEZ, Bram VAN GINNEKEN, Annette KOPP-SCHNEIDER and Bennett A. LANDMAN. BIAS: Transparent reporting of biomedical image analysis challenges. Medical Image Analysis. Elsevier, 2020, vol. 66, December, p. "101796", 7 pp. ISSN 1361-8415. doi:10.1016/
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Basic information
Original name BIAS: Transparent reporting of biomedical image analysis challenges
Authors MAIER-HEIN, Lena (276 Germany), Annika REINKE (276 Germany), Michal KOZUBEK (203 Czech Republic, guarantor, belonging to the institution), Anne L. MARTEL (124 Canada), Tal ARBEL (124 Canada), Matthias EISENMANN (276 Germany), Allan HANBURY (40 Austria), Pierre JANNIN (250 France), Henning MÜLLER (756 Switzerland), Sinan ONOGUR (276 Germany), Julio SAEZ-RODRIGUEZ (276 Germany), Bram VAN GINNEKEN (528 Netherlands), Annette KOPP-SCHNEIDER (276 Germany) and Bennett A. LANDMAN (840 United States of America).
Edition Medical Image Analysis, Elsevier, 2020, 1361-8415.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher Netherlands
Confidentiality degree is not subject to a state or trade secret
Impact factor Impact factor: 8.545
RIV identification code RIV/00216224:14330/20:00116355
Organization unit Faculty of Informatics
UT WoS 000579512600003
Keywords in English Biomedical challenges;Good scientific practice;Biomedical image analysis;Guideline
Tags cbia-web
Tags International impact, Reviewed
Changed by Changed by: RNDr. Pavel Šmerk, Ph.D., učo 3880. Changed: 10/5/2021 05:54.
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.
EF16_013/0001775, research and development projectName: Modernizace a podpora výzkumných aktivit národní infrastruktury pro biologické a medicínské zobrazování Czech-BioImaging
LTC17016, research and development projectName: Benchmarking algoritmů segmentace a sledování buněk
Investor: Ministry of Education, Youth and Sports of the CR, INTER-EXCELLENCE, INTER-COST
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