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  3. Understanding metric-related pitfalls in image analysis validation.

Understanding metric-related pitfalls in image analysis validation.

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DOI
10.48350/192846
Publisher DOI
10.1038/s41592-023-02150-0
PubMed ID
38347140
Abstract
Validation metrics are key for tracking scientific progress and bridging the current chasm between artificial intelligence research and its translation into practice. However, increasing evidence shows that, particularly in image analysis, metrics are often chosen inadequately. Although taking into account the individual strengths, weaknesses and limitations of validation metrics is a critical prerequisite to making educated choices, the relevant knowledge is currently scattered and poorly accessible to individual researchers. Based on a multistage Delphi process conducted by a multidisciplinary expert consortium as well as extensive community feedback, the present work provides a reliable and comprehensive common point of access to information on pitfalls related to validation metrics in image analysis. Although focused on biomedical image analysis, the addressed pitfalls generalize across application domains and are categorized according to a newly created, domain-agnostic taxonomy. The work serves to enhance global comprehension of a key topic in image analysis validation.
Date Issued
2024-02
Publication Type
Article
Subject(s)
600 Technology > 610 Medicine & health
Language(s)
en
Author(s)
Reinke, Annika
Tizabi, Minu D
Baumgartner, Michael
Eisenmann, Matthias
Heckmann-Nötzel, Doreen
Kavur, A Emre
Rädsch, Tim
Sudre, Carole H
Acion, Laura
Antonelli, Michela
Arbel, Tal
Bakas, Spyridon
Benis, Arriel
Buettner, Florian
Cardoso, M Jorge
Cheplygina, Veronika
Chen, Jianxu
Christodoulou, Evangelia
Cimini, Beth A
Farahani, Keyvan
Ferrer, Luciana
Galdran, Adrian
van Ginneken, Bram
Glocker, Ben
Godau, Patrick
Hashimoto, Daniel A
Hoffman, Michael M
Huisman, Merel
Isensee, Fabian
Jannin, Pierre
Kahn, Charles E
Kainmueller, Dagmar
Kainz, Bernhard
Karargyris, Alexandros
Kleesiek, Jens
Kofler, Florian
Kooi, Thijs
Kopp-Schneider, Annette
Kozubek, Michal
Kreshuk, Anna
Kurc, Tahsin
Landman, Bennett A
Litjens, Geert
Madani, Amin
Maier-Hein, Klaus
Martel, Anne L
Meijering, Erik
Menze, Bjoern
Moons, Karel G M
Müller, Henning
Nichyporuk, Brennan
Nickel, Felix
Petersen, Jens
Rafelski, Susanne M
Rajpoot, Nasir
Reyes, Mauricio  
ARTORG Center for Biomedical Engineering Research - Medical Image Analysis  
Universitätsklinik für Radio-Onkologie  
Riegler, Michael A
Rieke, Nicola
Saez-Rodriguez, Julio
Sánchez, Clara I
Shetty, Shravya
Summers, Ronald M
Taha, Abdel A
Tiulpin, Aleksei
Tsaftaris, Sotirios A
Van Calster, Ben
Varoquaux, Gaël
Yaniv, Ziv R
Jäger, Paul F
Maier-Hein, Lena
Additional Credits
ARTORG Center for Biomedical Engineering Research - Medical Image Analysis  
Universitätsklinik für Radio-Onkologie  
Journal
Nature methods
Publisher
Nature Publishing Group
ISSN
1548-7091
Access(Rights)
restricted
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