| 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, No 101796, p. 1-7. ISSN 1361-8415. Available from: https://dx.doi.org/10.1016/j.media.2020.101796. |
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@article{1677718,
author = {MaierandHein, Lena and Reinke, Annika and Kozubek, Michal and Martel, Anne L. and Arbel, Tal and Eisenmann, Matthias and Hanbury, Allan and Jannin, Pierre and Müller, Henning and Onogur, Sinan and SaezandRodriguez, Julio and van Ginneken, Bram and KoppandSchneider, Annette and Landman, Bennett A.},
article_number = {101796},
doi = {http://dx.doi.org/10.1016/j.media.2020.101796},
keywords = {Biomedical challenges;Good scientific practice;Biomedical image analysis;Guideline},
language = {eng},
issn = {1361-8415},
journal = {Medical Image Analysis},
title = {BIAS: Transparent reporting of biomedical image analysis challenges},
url = {https://doi.org/10.1016/j.media.2020.101796},
volume = {66},
year = {2020}
}
TY - JOUR
ID - 1677718
AU - 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.
PY - 2020
TI - BIAS: Transparent reporting of biomedical image analysis challenges
JF - Medical Image Analysis
VL - 66
IS - 101796
SP - 1-7
EP - 1-7
PB - Elsevier
SN - 13618415
KW - Biomedical challenges;Good scientific practice;Biomedical image analysis;Guideline
UR - https://doi.org/10.1016/j.media.2020.101796
L2 - https://doi.org/10.1016/j.media.2020.101796
N2 - 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.
ER -
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. \textit{Medical Image Analysis}. Elsevier, 2020, vol.~66, No~101796, p.~1-7. ISSN~1361-8415. Available from: https://dx.doi.org/10.1016/j.media.2020.101796.
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