Nature Communications (Jul 2022)
The Medical Segmentation Decathlon
- Michela Antonelli,
- Annika Reinke,
- Spyridon Bakas,
- Keyvan Farahani,
- Annette Kopp-Schneider,
- Bennett A. Landman,
- Geert Litjens,
- Bjoern Menze,
- Olaf Ronneberger,
- Ronald M. Summers,
- Bram van Ginneken,
- Michel Bilello,
- Patrick Bilic,
- Patrick F. Christ,
- Richard K. G. Do,
- Marc J. Gollub,
- Stephan H. Heckers,
- Henkjan Huisman,
- William R. Jarnagin,
- Maureen K. McHugo,
- Sandy Napel,
- Jennifer S. Golia Pernicka,
- Kawal Rhode,
- Catalina Tobon-Gomez,
- Eugene Vorontsov,
- James A. Meakin,
- Sebastien Ourselin,
- Manuel Wiesenfarth,
- Pablo Arbeláez,
- Byeonguk Bae,
- Sihong Chen,
- Laura Daza,
- Jianjiang Feng,
- Baochun He,
- Fabian Isensee,
- Yuanfeng Ji,
- Fucang Jia,
- Ildoo Kim,
- Klaus Maier-Hein,
- Dorit Merhof,
- Akshay Pai,
- Beomhee Park,
- Mathias Perslev,
- Ramin Rezaiifar,
- Oliver Rippel,
- Ignacio Sarasua,
- Wei Shen,
- Jaemin Son,
- Christian Wachinger,
- Liansheng Wang,
- Yan Wang,
- Yingda Xia,
- Daguang Xu,
- Zhanwei Xu,
- Yefeng Zheng,
- Amber L. Simpson,
- Lena Maier-Hein,
- M. Jorge Cardoso
Affiliations
- Michela Antonelli
- School of Biomedical Engineering & Imaging Sciences, King’s College London
- Annika Reinke
- Div. Computer Assisted Medical Interventions, German Cancer Research Center (DKFZ)
- Spyridon Bakas
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania
- Keyvan Farahani
- Center for Biomedical Informatics and Information Technology, National Cancer Institute (NIH)
- Annette Kopp-Schneider
- Div. Biostatistics, German Cancer Research Center (DKFZ)
- Bennett A. Landman
- Electrical Engineering and Computer Science, Vanderbilt University
- Geert Litjens
- Radboud University Medical Center, Radboud Institute for Health Sciences
- Bjoern Menze
- Quantitative Biomedicine, University of Zurich
- Olaf Ronneberger
- DeepMind
- Ronald M. Summers
- Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Department of Radiology and Imaging Sciences, National Institutes of Health Clinical Center (NIH)
- Bram van Ginneken
- Radboud University Medical Center, Radboud Institute for Health Sciences
- Michel Bilello
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania
- Patrick Bilic
- Department of Informatics, Technische Universität München
- Patrick F. Christ
- Department of Informatics, Technische Universität München
- Richard K. G. Do
- Department of Radiology, Memorial Sloan Kettering Cancer Center
- Marc J. Gollub
- Department of Radiology, Memorial Sloan Kettering Cancer Center
- Stephan H. Heckers
- Department of Psychiatry & Behavioral Sciences, Vanderbilt University Medical Center
- Henkjan Huisman
- Radboud University Medical Center, Radboud Institute for Health Sciences
- William R. Jarnagin
- Department of Surgery, Memorial Sloan Kettering Cancer Center
- Maureen K. McHugo
- Department of Psychiatry & Behavioral Sciences, Vanderbilt University Medical Center
- Sandy Napel
- Department of Radiology, Stanford University
- Jennifer S. Golia Pernicka
- Department of Radiology, Memorial Sloan Kettering Cancer Center
- Kawal Rhode
- School of Biomedical Engineering & Imaging Sciences, King’s College London
- Catalina Tobon-Gomez
- School of Biomedical Engineering & Imaging Sciences, King’s College London
- Eugene Vorontsov
- Department of Computer Science and Software Engineering, École Polytechnique de Montréal
- James A. Meakin
- Radboud University Medical Center, Radboud Institute for Health Sciences
- Sebastien Ourselin
- School of Biomedical Engineering & Imaging Sciences, King’s College London
- Manuel Wiesenfarth
- Div. Biostatistics, German Cancer Research Center (DKFZ)
- Pablo Arbeláez
- Universidad de los Andes
- Byeonguk Bae
- VUNO Inc.
- Sihong Chen
- Tencent Jarvis Lab
- Laura Daza
- Universidad de los Andes
- Jianjiang Feng
- Department of Automation, Tsinghua University
- Baochun He
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences
- Fabian Isensee
- HI Applied Computer Vision Lab, Division of Medical Image Computing, German Cancer Research Center (DKFZ)
- Yuanfeng Ji
- Department of Computer Science, Xiamen University
- Fucang Jia
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences
- Ildoo Kim
- Kakao Brain
- Klaus Maier-Hein
- Cerebriu A/S
- Dorit Merhof
- Institute of Imaging & Computer Vision, RWTH Aachen University
- Akshay Pai
- Cerebriu A/S
- Beomhee Park
- VUNO Inc.
- Mathias Perslev
- Department of Computer Science, University of Copenhagen
- Ramin Rezaiifar
- MaaDoTaa.com
- Oliver Rippel
- Institute of Imaging & Computer Vision, RWTH Aachen University
- Ignacio Sarasua
- Lab for Artificial Intelligence in Medical Imaging (AI-Med), Department of Child and Adolescent Psychiatry, University Hospital
- Wei Shen
- MoE Key Lab of Artificial Intelligence, AI Institute, Shanghai Jiao Tong University
- Jaemin Son
- VUNO Inc.
- Christian Wachinger
- Lab for Artificial Intelligence in Medical Imaging (AI-Med), Department of Child and Adolescent Psychiatry, University Hospital
- Liansheng Wang
- Department of Computer Science, Xiamen University
- Yan Wang
- Shanghai Key Laboratory of Multidimensional Information Processing, East China Normal University
- Yingda Xia
- Johns Hopkins University
- Daguang Xu
- NVIDIA
- Zhanwei Xu
- Department of Automation, Tsinghua University
- Yefeng Zheng
- Tencent Jarvis Lab
- Amber L. Simpson
- School of Computing/Department of Biomedical and Molecular Sciences, Queen’s University
- Lena Maier-Hein
- Div. Computer Assisted Medical Interventions, German Cancer Research Center (DKFZ)
- M. Jorge Cardoso
- School of Biomedical Engineering & Imaging Sciences, King’s College London
- DOI
- https://doi.org/10.1038/s41467-022-30695-9
- Journal volume & issue
-
Vol. 13,
no. 1
pp. 1 – 13
Abstract
International challenges have become the de facto standard for comparative assessment of image analysis algorithms. Here, the authors present the results of a biomedical image segmentation challenge, showing that a method capable of performing well on multiple tasks will generalize well to a previously unseen task.
