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Improving Automated Glioma Segmentation in Routine Clinical Use Through Artificial Intelligence-Based Replacement of Missing Sequences With Synthetic Magnetic Resonance Imaging Scans.
Thomas, Marie Franziska; Kofler, Florian; Grundl, Lioba; Finck, Tom; Li, Hongwei; Zimmer, Claus; Menze, Björn; Wiestler, Benedikt.
Afiliação
  • Thomas MF; From the Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technical University of Munich, Munich.
  • Grundl L; From the Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technical University of Munich, Munich.
  • Finck T; From the Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technical University of Munich, Munich.
  • Li H; Image-Based Biomedical Modeling, Chair for Computer Aided Medical Procedures and Augmented Reality, Technical University of Munich, Garching.
  • Zimmer C; From the Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technical University of Munich, Munich.
  • Menze B; Image-Based Biomedical Modeling, Chair for Computer Aided Medical Procedures and Augmented Reality, Technical University of Munich, Garching.
Invest Radiol ; 57(3): 187-193, 2022 03 01.
Article em En | MEDLINE | ID: mdl-34652289
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias Encefálicas / Glioma Tipo de estudo: Prognostic_studies / Qualitative_research Limite: Humans Idioma: En Revista: Invest Radiol Ano de publicação: 2022 Tipo de documento: Article
Texto completo
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias Encefálicas / Glioma Tipo de estudo: Prognostic_studies / Qualitative_research Limite: Humans Idioma: En Revista: Invest Radiol Ano de publicação: 2022 Tipo de documento: Article