Detailed Information on Publication Record
2018
Why rankings of biomedical image analysis competitions should be interpreted with care
MAIER-HEIN, Lena, Matthias EISENMANN, Annika REINKE, Sinan ONOGUR, Marko STANKOVIC et. al.Basic information
Original name
Why rankings of biomedical image analysis competitions should be interpreted with care
Authors
MAIER-HEIN, Lena, Matthias EISENMANN, Annika REINKE, Sinan ONOGUR, Marko STANKOVIC, Patrick SCHOLZ, Tal ARBEL, Hrvoje BOGUNOVIC, Andrew BRADLEY, Aaron CARASS, Carolin FELDMANN, Alejandro FRANGI, Peter FULL, Bram VAN GINNEKEN, Allan HANBURY, Katrin HONAUER, Michal KOZUBEK (203 Czech Republic, guarantor, belonging to the institution), Bennett LANDMAN, Keno MÄRZ, Oskar MAIER, Klaus MAIER-HEIN, Bjoern MENZE, Henning MÜLLER, Peter NEHER, Wiro NIESSEN, Nasir RAJPOOT, Gregory SHARP, Korsuk SIRINUKUNWATTANA, Stefanie SPEIDEL, Christian STOCK, Danail STOYANOV, Abdel Aziz TAHA, Fons VAN DER SOMMEN, Ching-Wei WANG, Marc-André WEBER, Guoyan ZHENG, Pierre JANNIN and Annette KOPP-SCHNEIDER
Edition
Nature Communications, Nature Publishing Group, 2018, 2041-1723
Other information
Language
English
Type of outcome
Článek v odborném periodiku
Field of Study
10201 Computer sciences, information science, bioinformatics
Country of publisher
Switzerland
Confidentiality degree
není předmětem státního či obchodního tajemství
References:
Impact factor
Impact factor: 11.878
RIV identification code
RIV/00216224:14330/18:00101338
Organization unit
Faculty of Informatics
UT WoS
000452282700012
Keywords in English
biomedical image analysis; benchmarking; challenge
Tags
Tags
International impact, Reviewed
Změněno: 31/12/2018 08:54, RNDr. Pavel Šmerk, Ph.D.
Abstract
V originále
International challenges have become the standard for validation of biomedical image analysis methods. Given their scientific impact, it is surprising that a critical analysis of common practices related to the organization of challenges has not yet been performed. In this paper, we present a comprehensive analysis of biomedical image analysis challenges conducted up to now. We demonstrate the importance of challenges and show that the lack of quality control has critical consequences. First, reproducibility and interpretation of the results is often hampered as only a fraction of relevant information is typically provided. Second, the rank of an algorithm is generally not robust to a number of variables such as the test data used for validation, the ranking scheme applied and the observers that make the reference annotations. To overcome these problems, we recommend best practice guidelines and define open research questions to be addressed in the future.
Links
GBP302/12/G157, research and development project |
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LTC17016, research and development project |
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