The Brain Tumor Segmentation (BraTS) Challenge 2023: Brain MR Image Synthesis for Tumor Segmentation (BraSyn) .

Autor: Li HB; University of Zurich, Switzerland.; Department of Informatics, Technical University Munich, Germany.; Klinikum rechts der Isar, Technical University of Munich, Germany., Conte GM; Mayo Clinic, Rochester, USA., Hu Q; University of Zurich, Switzerland.; Department of Informatics, Technical University Munich, Germany.; Klinikum rechts der Isar, Technical University of Munich, Germany.; Mayo Clinic, Rochester, USA.; Helmholtz AI, Helmholtz Munich, Germany.; TranslaTUM - Central Institute for Translational Cancer Research, Technical University of Munich, Germany.; Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Germany.; Children's National Hospital, Washington DC, USA and George Washington University, USA.; Finnish Center for Artificial Intelligence, Finland.; Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School, USA.; Medical Artificial Intelligence (MAI) Lab, Crestview Radiology, Lagos, Nigeria.; Children's National Hospital, Washington DC, USA.; George Washington University, Washington DC, USA.; Center for AI and Data Science for Integrated Diagnostics (AI2D) I& Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA.; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.; Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.; Yale University, New Haven, CT, USA.; Children's Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA, USA.; Duke University Medical Center, Department of Radiation Oncology, USA.; Athinoula A Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA.; Department of Neuroradiology, Technical University of Munich, Munich, Germany.; Mercy Catholic Medical Center, Darby, PA, USA.; Cancer Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, MD 20814, USA.; Sage Bionetworks, USA.; Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, USA.; Center for Global Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.; Duke University Medical Center, Department of Radiology, USA.; Department of Applied Mathematics and Computer Science, Technical University of Denmark, Denmark.; Montreal Neurological Institute (MNI), McGill University, Montreal, QC, Canada.; PrecisionFDA, U.S. Food and Drug Administration, Silver Spring, MD, USA.; Booz Allen Hamilton, McLean, VA, USA.; Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, Frederick, MD 21701, USA.; Department of Neurology, The University of Alabama at Birmingham, Birmingham, AL, USA.; Institute for Surgical Technology and Biomechanics, University of Bern, Bern, Switzerland.; Support Centre for Advanced Neuroimaging Inselspital, Institute for Diagnostic and Interventional Neuroradiology, Bern University Hospital, Bern, Switzerland.; University of Pittsburgh Medical Center, PA, USA.; Department of Diagnostic Radiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA.; Department of Psychology, Washington University, St. Louis, MO, USA.; Neuroimaging Informatics and Analysis Center, Washington University, St. Louis, MO, USA.; Department of Radiology, Washington University, St. Louis, MO, USA.; Institute of Diagnostic and Interventional Radiology, Pediatric Radiology and Neuroradiology, University Medical Center Rostock, Ernst-Heydemann-Str. 6, 18057 Rostock, Germany.; Tata Memorial Centre, Homi Bhabha National Institute, Mumbai, India.; University of California San Francisco, CA, USA.; University of Toronto, Toronto, ON, Canada.; University of Debrecen, Hungary Stony Brook University, NY, USA., Anwar SM; Children's National Hospital, Washington DC, USA.; George Washington University, Washington DC, USA., Kofler F; Helmholtz AI, Helmholtz Munich, Germany.; Department of Informatics, Technical University Munich, Germany.; TranslaTUM - Central Institute for Translational Cancer Research, Technical University of Munich, Germany.; Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Germany., Ezhov I; Department of Informatics, Technical University Munich, Germany., van Leemput K; Finnish Center for Artificial Intelligence, Finland., Piraud M; Helmholtz AI, Helmholtz Munich, Germany., Diaz M; Sage Bionetworks, USA., Cole B; Sage Bionetworks, USA., Calabrese E; Duke University Medical Center, Department of Radiology, USA.; University of California San Francisco, CA, USA., Rudie J; University of California San Francisco, CA, USA., Meissen F; Department of Informatics, Technical University Munich, Germany., Adewole M; Medical Artificial Intelligence (MAI) Lab, Crestview Radiology, Lagos, Nigeria., Janas A; Yale University, New Haven, CT, USA., Kazerooni AF; Children's Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA, USA.; Center for AI and Data Science for Integrated Diagnostics (AI2D) I& Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA., LaBella D; Duke University Medical Center, Department of Radiation Oncology, USA., Moawad AW; Mercy Catholic Medical Center, Darby, PA, USA., Farahani K; Cancer Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, MD 20814, USA., Eddy J; Sage Bionetworks, USA., Bergquist T; Sage Bionetworks, USA., Chung V; Sage Bionetworks, USA., Shinohara RT; Center for AI and Data Science for Integrated Diagnostics (AI2D) I& Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA.; Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, USA., Dako F; Center for Global Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA., Wiggins W; Duke University Medical Center, Department of Radiology, USA., Reitman Z; Duke University Medical Center, Department of Radiation Oncology, USA., Wang C; Duke University Medical Center, Department of Radiation Oncology, USA., Liu X; Children's National Hospital, Washington DC, USA.; George Washington University, Washington DC, USA., Jiang Z; Children's National Hospital, Washington DC, USA.; George Washington University, Washington DC, USA., Familiar A; Children's Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA, USA., Johanson E; PrecisionFDA, U.S. Food and Drug Administration, Silver Spring, MD, USA., Meier Z; Booz Allen Hamilton, McLean, VA, USA., Davatzikos C; Center for AI and Data Science for Integrated Diagnostics (AI2D) I& Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA.; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA., Freymann J; Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, Frederick, MD 21701, USA.; Cancer Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, MD 20814, USA., Kirby J; Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, Frederick, MD 21701, USA.; Cancer Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, MD 20814, USA., Bilello M; Center for AI and Data Science for Integrated Diagnostics (AI2D) I& Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA.; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA., Fathallah-Shaykh HM; Department of Neurology, The University of Alabama at Birmingham, Birmingham, AL, USA., Wiest R; Institute for Surgical Technology and Biomechanics, University of Bern, Bern, Switzerland.; Support Centre for Advanced Neuroimaging Inselspital, Institute for Diagnostic and Interventional Neuroradiology, Bern University Hospital, Bern, Switzerland., Kirschke J; Department of Neuroradiology, Technical University of Munich, Munich, Germany., Colen RR; University of Pittsburgh Medical Center, PA, USA.; Department of Diagnostic Radiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA., Kotrotsou A; Department of Diagnostic Radiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA., Lamontagne P; Department of Psychology, Washington University, St. Louis, MO, USA., Marcus D; Neuroimaging Informatics and Analysis Center, Washington University, St. Louis, MO, USA.; Department of Radiology, Washington University, St. Louis, MO, USA., Milchenko M; Neuroimaging Informatics and Analysis Center, Washington University, St. Louis, MO, USA.; Department of Radiology, Washington University, St. Louis, MO, USA., Nazeri A; Department of Radiology, Washington University, St. Louis, MO, USA., Weber MA; Institute of Diagnostic and Interventional Radiology, Pediatric Radiology and Neuroradiology, University Medical Center Rostock, Ernst-Heydemann-Str. 6, 18057 Rostock, Germany., Mahajan A; Tata Memorial Centre, Homi Bhabha National Institute, Mumbai, India., Mohan S; Center for AI and Data Science for Integrated Diagnostics (AI2D) I& Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA.; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA., Mongan J; University of California San Francisco, CA, USA., Hess C; University of California San Francisco, CA, USA., Cha S; University of California San Francisco, CA, USA., Villanueva-Meyer J; University of California San Francisco, CA, USA., Colak E; University of Toronto, Toronto, ON, Canada., Crivellaro P; University of Toronto, Toronto, ON, Canada., Jakab A; University of Debrecen, Hungary Stony Brook University, NY, USA., Albrecht J; Sage Bionetworks, USA., Anazodo U; Montreal Neurological Institute (MNI), McGill University, Montreal, QC, Canada., Aboian M; Yale University, New Haven, CT, USA., Yu T; Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School, USA., Chung V; Sage Bionetworks, USA., Bergquist T; Sage Bionetworks, USA., Eddy J; Sage Bionetworks, USA., Albrecht J; Sage Bionetworks, USA., Baid U; Center for AI and Data Science for Integrated Diagnostics (AI2D) I& Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA.; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.; Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA., Bakas S; Center for AI and Data Science for Integrated Diagnostics (AI2D) I& Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA.; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.; Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA., Linguraru MG; Children's National Hospital, Washington DC, USA and George Washington University, USA., Menze B; University of Zurich, Switzerland., Iglesias JE; Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School, USA., Wiestler B; Klinikum rechts der Isar, Technical University of Munich, Germany.
Jazyk: angličtina
Zdroj: ArXiv [ArXiv] 2024 Nov 24. Date of Electronic Publication: 2024 Nov 24.
Abstrakt: Automated brain tumor segmentation methods have become well-established and reached performance levels offering clear clinical utility. These methods typically rely on four input magnetic resonance imaging (MRI) modalities: T1-weighted images with and without contrast enhancement, T2-weighted images, and FLAIR images. However, some sequences are often missing in clinical practice due to time constraints or image artifacts, such as patient motion. Consequently, the ability to substitute missing modalities and gain segmentation performance is highly desirable and necessary for the broader adoption of these algorithms in the clinical routine. In this work, we present the establishment of the Brain MR Image Synthesis Benchmark (BraSyn) in conjunction with the Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2023. The primary objective of this challenge is to evaluate image synthesis methods that can realistically generate missing MRI modalities when multiple available images are provided. The ultimate aim is to facilitate automated brain tumor segmentation pipelines. The image dataset used in the benchmark is diverse and multi-modal, created through collaboration with various hospitals and research institutions.
Databáze: MEDLINE