Mitosis domain generalization in histopathology images — The MIDOG challenge

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Bibliographic Details
Published inMedical Image Analysis Vol. 84; p. 102699
Main Authors Marc Aubreville, Nikolas Stathonikos, Christof A. Bertram, Robert Klopfleisch, Natalie ter Hoeve, Francesco Ciompi, Frauke Wilm, Christian Marzahl, Taryn A. Donovan, Andreas Maier, Jack Breen, Nishant Ravikumar, Youjin Chung, Jinah Park, Ramin Nateghi, Fattaneh Pourakpour, Rutger H.J. Fick, Saima Ben Hadj, Mostafa Jahanifar, Adam Shephard, Jakob Dexl, Thomas Wittenberg, Satoshi Kondo, Maxime W. Lafarge, Viktor H. Koelzer, Jingtang Liang, Yubo Wang, Xi Long, Jingxin Liu, Salar Razavi, April Khademi, Sen Yang, Xiyue Wang, Ramona Erber, Andrea Klang, Karoline Lipnik, Pompei Bolfa, Michael J. Dark, Gabriel Wasinger, Mitko Veta, Katharina Breininger
Format Journal Article
LanguageJapanese
Published Elsevier BV 01.02.2023
Subjects
Algorithms
Challenge
Computer Graphics and Computer-Aided Design
Computer Science - Computer Vision and Pattern Recognition
Computer Vision and Pattern Recognition
Computer Vision and Pattern Recognition (cs.CV)
Deep Learning
Domain generalization
Electrical Engineering and Systems Science - Image and Video Processing
FOS: Biological sciences
FOS: Computer and information sciences
FOS: Electrical engineering, electronic engineering, information engineering
FOS: Physical sciences
Health Informatics
Histopathology
Humans
Image and Video Processing (eess.IV)
Medical Physics (physics.med-ph)
Mitosis
Neoplasm Grading
Physics - Medical Physics
Prognosis
Quantitative Biology - Quantitative Methods
Quantitative Methods (q-bio.QM)
Radboudumc 9: Rare cancers Pathology
Radiological and Ultrasound Technology
Radiology Nuclear Medicine and imaging
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ISSN:1361-8415
DOI:10.1016/j.media.2022.102699