Peer-Reviewed Publication
Med Image Anal2026;114104282.November 1, 2026Journal Article
crossMoDA challenge: Evolution of cross-modality domain adaptation techniques for vestibular schwannoma and cochlea segmentation from 2021 to 2023.
Navodini Wijethilake1, Reuben Dorent2, Marina Ivory3, Aaron Kujawa3, Stefan Cornelissen4, Patrick Langenhuizen4, Mohamed Okasha5, Anna Oviedova5, Hexin Dong6, Bogyeong Kang7, Guillaume Sallé8, Luyi Han9, Ziyuan Zhao10, Han Liu11, Yubo Fan11, Tao Yang12, Shahad Hardan13, Hussain Alasmawi13, Santosh Sanjeev13, Yuzhou Zhuang14, Satoshi Kondo15, Maria Baldeon Calisto16, Shaikh Muhammad Uzair Noman17, Cancan Chen18, Ipek Oguz11, Rongguo Zhang19, Mina Rezaei17, Susana K Lai-Yuen20, Satoshi Kasai21, Yunzhi Huang22, Chih-Cheng Hung23, Mohammad Yaqub13, Lisheng Wang12, Benoit M Dawant11, Cuntai Guan24, Ritse Mann9, Vincent Jaouen8, Tae-Eui Kam7, Li Zhang25, Jonathan Shapey26, Tom Vercauteren3
1School of BMEIS, King's College London, London, United Kingdom. Electronic address: navodini.wijethilake@kcl.ac.uk.
2Harvard University, USA.
3School of BMEIS, King's College London, London, United Kingdom.
4Elisabeth-TweeSteden Hospital, Tilburg, Netherlands.
5King's College Hospital, London, United Kingdom.
6Center for Data Science, Peking University, Beijing, China.
7Department of Artificial Intelligence, Korea University, Seoul, Republic of Korea.
8UMR 1101 Inserm LaTIM, Université de Bretagne Occidentale, IMT Atlantique, Brest, France.
9Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Geert Grooteplein 10, 6525 GA, Nijmegen, The Netherlands; Department of Radiology, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands.
10Institute for Infocomm Research (I(2)R), A*STAR, Singapore; Artificial Intelligence, Analytics And Informatics (AI(3)), A*STAR, Singapore; Nanyang Technological University, Singapore.
11Vanderbilt University, USA.
12Department of Automation, Shanghai Jiao Tong University, Shanghai, China.
13Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab Emirates.
14School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China.
15Muroran Institute of Technology, Hokkaido, Japan.
16Universidad San Francisco de Quito, Diego de Robles s/n y Vía Interoceánica, Quito, Ecuador.
17Ludwig-Maximilians-Universität München, Germany.
18Infervision Advanced Research Institute, Beijing, China.
19Infervision Advanced Research Institute, Beijing, China; Academy for Multidisciplinary Studies, Capital Normal University, Beijing, China.
20University of South Florida, Tampa, FL, USA.
21Niigata University of Health and Welfare, Niigata, Japan.
22School of Automation, Nanjing University of Information Science and Technology, Nanjing 210044, China.
23Center for Machine Vision and Security Research, Kennesaw State University, Marietta, MA 30060, USA.
24Nanyang Technological University, Singapore.
25Center for Data Science, Peking University, Beijing, China; Center for Data Science in Health and Medicine, Peking University, Beijing, China.
26School of BMEIS, King's College London, London, United Kingdom; King's College Hospital, London, United Kingdom.
Abstract
The cross-Modality Domain Adaptation (crossMoDA) challenge series, initiated in 2021 in conjunction with the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), focuses on unsupervised cross-modality segmentation, learning from contrast-enhanced T1 (ceT1) and transferring to T2 MRI. The task is an extreme example of domain shift chosen to serve as a mea…
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