Advances in Automated Fetal Brain MRI Segmentation and Biometry: Insights from the FeTA 2024 Challenge
自动化胎儿脑MRI分割与生物测量的进展：来自FeTA 2024挑战的见解
机构 * organization= Department of Radiology, Lausanne University Hospital ； University of Lausanne , city= Lausanne , country= Switzerland ； organization= CIBM Center for Biomedical Imaging , city= Lausanne , country= Switzerland ； organization= Department of Early Life Imaging, School of Biomedical Engineering \& Imaging Sciences, King’s College London , city= London , country= UK ； organization= Smart Imaging Lab, University Hospital Erlangen , city= Erlangen , country= Germany ； organization= Center for MR-Research, University Children’s Hospital Zurich, University of Zurich , city= Zurich , country= Switzerland ； organization= Neuroscience Center Zurich, University of Zurich , city= Zurich , country= Switzerland ； organization= National Heart \& Lung Institute, Imperial College London , city= London , country= UK ； organization= University of California, San Francisco ； UCSF Benioff Children’s Hospital , city= San Francisco , state= California , country= USA ； organization= Department of Quantitative Biomedicine, University of Zurich , city= Zurich , country= Switzerland ； organization= Department of Informatics, Technical University of Munich , city= Munich , country= Germany ； organization= Boston Children’s Hospital, Harvard Medical School , city= Boston , state= Massachusetts , country= USA ； organization= Neuroimaging Unit, Scientific Institute IRCCS E. Medea , city= Bosisio Parini , country= Italy ； organization= Department of Informatics, Systems ； Communication, University of Milano Bicocca , city= Milan , country= Italy ； organization= Research Institute of Computer Vision ； organization= BCN MedTech, Department of Engineering, Universitat Pompeu Fabra , city= Barcelona , country= Spain ； organization= Department of Information Engineering, University of Padova , city= Padova , country= Italy ； organization= Institut Pasteur, Université Paris Cité, CNRS UMR 3571, Decision ； organization= Inria, HeKA, PariSantéCampus , city= Paris , country= France ； organization= L. D. College of Engineering , city= Gujarat , country= India ； organization= Medical Faculty Heidelberg, Heidelberg University , addressline= Pattern Analysis ； Learning Group, Department of Radiation Oncology, Heidelberg University Hospital , city= Heidelberg , country= Germany ； organization= Canon Medical Systems (China) Co., Ltd , city= , country= China ； organization= Faculty of Electrical Engineering, University of Ljubljana , city= Ljubljana , country= Slovenia ； organization= Department of Radiology, Seoul National University Hospital , city= Seoul , country= South Korea ； organization= School of Mechanical ； Electrical Engineering, University of Electronic Science ； organization= School of Computer Science, Wuhan University , city= Wuhan , country= China ； Developmental Science Center, Boston Children’s Hospital, Harvard Medical School , city= Boston , state= Massachusetts , country= USA ； organization= Hawkes Institute, Department of Computer Science, University College London , city= London , country= UK ； organization= Laboratory for Computational Neuroimaging, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital/Harvard Medical School , city= Charlestown , state= Massachusetts , country= USA ； organization= Department of Biomedical Imaging ； Image-guided Therapy, Computational Imaging Research Lab (CIR), Early Life Image Analysis Group, Medical University of Vienna , city= Vienna , country= Austria ； organization= University Research Priority Project Adaptive Brain Circuits in Development ； Learning (AdaBD), University of Zurich , city= Zurich , country= Switzerland ； organization= Sagol Brain Institute, Tel Aviv Sourasky Medical Center ； School of EE, Tel-Aviv University , city= Tel-Aviv , country= Israel ； organization= Department of Medical Imaging Sciences, The Faculty of Social Welfare ； Health Sciences, University of Haifa , city= Haifa , country= Israel ； Faculty of Medicine ； Sagol School of Neuroscience, Tel-Aviv University , city= Tel-Aviv , country= Israel ； organization= Department Woman-Mother-Child, CHUV , city= Lausanne , country= Switzerland ； organization= BCNatal Fetal Medicine Research Center (Hospital Clínic ； Hospital Sant Joan de Déu), Universitat de Barcelona , city= Barcelona , country= Spain ； organization= German Cancer Research Center (DKFZ) Heidelberg, Division of Medical Image Computing , city= Heidelberg , country= Germany ； organization= Helmholtz Imaging, German Cancer Research Center (DKFZ) , city= Heidelberg , country= Germany ； organization= Faculty of Mathematics ； Computer Science, Heidelberg University , city= Heidelberg , country= Germany ； organization= University of Zurich , city= Zurich , country= Switzerland ； organization= Croatian Institute for Brain Research, School of Medicine, University of Zagreb , city= Zagreb , country= Croatia ； organization= Department of Biomedical Engineering, School of Biomedical Engineering \& Imaging Sciences, King’s College , city= London , country= United Kingdom ； Musculoskeletal Radiology, Medical University of Vienna , city= Vienna , country= Austria ； organization= Division of Newborn Medicine, Boston Children’s Hospital, Harvard Medical School , city= Boston , state= Massachusetts , country= USA ； organization= Department of Radiology, Boston Children’s Hospital, Harvard Medical School , city= Boston , state= Massachusetts , country= USA
AI总结 FeTA 2024挑战通过引入生物测量预测和低场MRI数据，推动了胎儿脑MRI分割与生物测量的自动化进展，揭示了拓扑差异和成像系统对分割性能的影响。
