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Why rankings of biomedical image analysis competitions should be interpreted with care

Title: Why rankings of biomedical image analysis competitions should be interpreted with care
Authors: Maier-Hein, L; Eisenmann, M; Reinke, A; Onogur, S; Stankovic, M; Scholz, P; Arbel, T; Bogunovic, H; Bradley, AP; Carass, A; Feldmann, C; Frangi, AF; Full, PM; Ginneken, BTJ; Hanbury, A; Honauer, K; Kozubek, M; Landman, BA; Marz, K; Maier, O; Maier-Hein, K; Menze, BH; Müller, Henning; Neher, PF; Niessen, Wiro; Rajpoot, N; Sharp, GC; Sirinukunwattana, K; Speidel, S; Stock, C; Stoyanov, D; Taha, AA; Van der Sommen, F; Wang, CW; Weber, MA; Zheng, G; Jannin, P; Kopp-Schneider, A
Source: Maier-Hein, L, Eisenmann, M, Reinke, A, Onogur, S, Stankovic, M, Scholz, P, Arbel, T, Bogunovic, H, Bradley, AP, Carass, A, Feldmann, C, Frangi, AF, Full, PM, Ginneken, BTJ, Hanbury, A, Honauer, K, Kozubek, M, Landman, BA, Marz, K, Maier, O, Maier-Hein, K, Menze, BH, Müller, H, Neher, PF, Niessen, W, Rajpoot, N, Sharp, GC, Sirinukunwattana, K, Speidel, S, Stock, C, Stoyanov, D, Taha, AA, Van der Sommen, F, Wang, CW, Weber, MA, Zheng, G, Jannin, P & Kopp-Schneider, A 2018, 'Why rankings of biomedical image analysis competitions should be interpreted with care', Nature Communications, vol. 9, 5217. https://doi.org/10.1038/s41467-018-07619-7
Publication Year: 2018
Subject Terms: /dk/atira/pure/keywords/researchprograms/AFL001000/EMCNIHES033002; name=EMC NIHES-03-30-02; /dk/atira/pure/keywords/researchprograms/AFL001000/EMCNIHES033003; name=EMC NIHES-03-30-03
Description: 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.
Document Type: article in journal/newspaper
File Description: application/pdf
Language: English
ISSN: 2041-1723
Relation: info:eu-repo/semantics/altIdentifier/pmid/30523263; info:eu-repo/semantics/altIdentifier/pissn/2041-1723; info:eu-repo/semantics/altIdentifier/eissn/2041-1723
DOI: 10.1038/s41467-018-07619-7
Availability: https://pure.eur.nl/en/publications/738d7998-f514-4d1b-8b32-d1994ff175d8; https://doi.org/10.1038/s41467-018-07619-7; https://pure.eur.nl/ws/files/48082104/Repub-113081-OA.pdf; https://hdl.handle.net/1765/113081
Rights: info:eu-repo/semantics/openAccess ; http://creativecommons.org/licenses/by/4.0/
Accession Number: edsbas.5F69A034
Database: BASE