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CrossMoDA 2021 challenge: Benchmark of cross-modality domain adaptation techniques for vestibular schwannoma and cochlea segmentation.
Dorent, Reuben; Kujawa, Aaron; Ivory, Marina; Bakas, Spyridon; Rieke, Nicola; Joutard, Samuel; Glocker, Ben; Cardoso, Jorge; Modat, Marc; Batmanghelich, Kayhan; Belkov, Arseniy; Calisto, Maria Baldeon; Choi, Jae Won; Dawant, Benoit M; Dong, Hexin; Escalera, Sergio; Fan, Yubo; Hansen, Lasse; Heinrich, Mattias P; Joshi, Smriti; Kashtanova, Victoriya; Kim, Hyeon Gyu; Kondo, Satoshi; Kruse, Christian N; Lai-Yuen, Susana K; Li, Hao; Liu, Han; Ly, Buntheng; Oguz, Ipek; Shin, Hyungseob; Shirokikh, Boris; Su, Zixian; Wang, Guotai; Wu, Jianghao; Xu, Yanwu; Yao, Kai; Zhang, Li; Ourselin, Sébastien; Shapey, Jonathan; Vercauteren, Tom.
Afiliação
  • Dorent R; School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom. Electronic address: reuben.dorent@kcl.ac.uk.
  • Kujawa A; School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
  • Ivory M; School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
  • Bakas S; Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, USA; Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Radiology, Perelman School of Medicine, Universit
  • Rieke N; NVIDIA, Germany.
  • Joutard S; School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
  • Glocker B; Department of Computing, Imperial College London, Department of Computing, London, United Kingdom.
  • Cardoso J; School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
  • Modat M; School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
  • Batmanghelich K; Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, USA.
  • Belkov A; Moscow Institute of Physics and Technology, Moscow, Russia.
  • Calisto MB; Universidad San Francisco de Quito, Quito, Ecuador.
  • Choi JW; Department of Radiology, Armed Forces Yangju Hospital, Yangju, Republic of Korea.
  • Dawant BM; Vanderbilt University, Nashville, USA.
  • Dong H; Center for Data Science, Peking University, Beijing, China.
  • Escalera S; Artificial Intelligence in Medicine Lab (BCN-AIM) and Human Behavior Analysis Lab (HuPBA), Universitat de Barcelona, Barcelona, Spain.
  • Fan Y; Vanderbilt University, Nashville, USA.
  • Hansen L; Institute of Medical Informatics, Universität zu Lübeck, Germany.
  • Heinrich MP; Institute of Medical Informatics, Universität zu Lübeck, Germany.
  • Joshi S; Artificial Intelligence in Medicine Lab (BCN-AIM) and Human Behavior Analysis Lab (HuPBA), Universitat de Barcelona, Barcelona, Spain.
  • Kashtanova V; Inria, Université Côte d'Azur, Sophia Antipolis, France.
  • Kim HG; School of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea.
  • Kondo S; Muroran Institute of Technology, Muroran, Japan.
  • Kruse CN; Institute of Medical Informatics, Universität zu Lübeck, Germany.
  • Lai-Yuen SK; University of South Florida, Tampa, USA.
  • Li H; Vanderbilt University, Nashville, USA.
  • Liu H; Vanderbilt University, Nashville, USA.
  • Ly B; Inria, Université Côte d'Azur, Sophia Antipolis, France.
  • Oguz I; Vanderbilt University, Nashville, USA.
  • Shin H; School of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea.
  • Shirokikh B; Skolkovo Institute of Science and Technology, Moscow, Russia; Artificial Intelligence Research Institute (AIRI), Moscow, Russia.
  • Su Z; University of Liverpool, Liverpool, United Kingdom; School of Advanced Technology, Xi'an Jiaotong-Liverpool University, Suzhou, China.
  • Wang G; School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China.
  • Wu J; School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China.
  • Xu Y; Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, USA.
  • Yao K; University of Liverpool, Liverpool, United Kingdom; School of Advanced Technology, Xi'an Jiaotong-Liverpool University, Suzhou, China.
  • Zhang L; Center for Data Science, Peking University, Beijing, China.
  • Ourselin S; School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
  • Shapey J; School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom; Department of Neurosurgery, King's College Hospital, London, United Kingdom.
  • Vercauteren T; School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
Med Image Anal ; 83: 102628, 2023 01.
Article em En | MEDLINE | ID: mdl-36283200
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Texto completo: 1 Coleções: 01-internacional Temas: Geral / Tipos_de_cancer / Outros_tipos Base de dados: MEDLINE Assunto principal: Neuroma Acústico Tipo de estudo: Guideline / Prognostic_studies Limite: Humans Idioma: En Revista: Med Image Anal Assunto da revista: DIAGNOSTICO POR IMAGEM Ano de publicação: 2023 Tipo de documento: Article
Texto completo
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XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Temas: Geral / Tipos_de_cancer / Outros_tipos Base de dados: MEDLINE Assunto principal: Neuroma Acústico Tipo de estudo: Guideline / Prognostic_studies Limite: Humans Idioma: En Revista: Med Image Anal Assunto da revista: DIAGNOSTICO POR IMAGEM Ano de publicação: 2023 Tipo de documento: Article