TY  - JOUR
AU  - Maier-Hein, Lena
AU  - Reinke, Annika
AU  - Kozubek, Michal
AU  - Martel, Anne L
AU  - Arbel, Tal
AU  - Eisenmann, Matthias
AU  - Hanbury, Allan
AU  - Jannin, Pierre
AU  - Müller, Henning
AU  - Onogur, Sinan
AU  - Saez-Rodriguez, Julio
AU  - van Ginneken, Bram
AU  - Kopp-Schneider, Annette
AU  - Landman, Bennett A
TI  - BIAS: Transparent reporting of biomedical image analysis challenges.
JO  - Medical image analysis
VL  - 66
SN  - 1361-8415
CY  - Amsterdam [u.a.]
PB  - Elsevier Science
M1  - DKFZ-2020-01979
SP  - 101796
PY  - 2020
N1  - #EA:E130#
AB  - 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.
LB  - PUB:(DE-HGF)16
C6  - pmid:32911207
DO  - DOI:10.1016/j.media.2020.101796
UR  - https://inrepo02.dkfz.de/record/163703
ER  -