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Improving automatic liver tumor segmentation in late-phase MRI using multi-model training and 3D convolutional neural networks.
Hänsch, Annika; Chlebus, Grzegorz; Meine, Hans; Thielke, Felix; Kock, Farina; Paulus, Tobias; Abolmaali, Nasreddin; Schenk, Andrea.
Afiliação
  • Hänsch A; Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany. annika.haensch@mevis.fraunhofer.de.
  • Chlebus G; Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany.
  • Meine H; Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany.
  • Thielke F; Medical Image Computing Group, University of Bremen, Bremen, Germany.
  • Kock F; Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany.
  • Paulus T; Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany.
  • Abolmaali N; Institut für Diagnostische und Interventionelle Radiologie und Nuklearmedizin, Katholisches Klinikum Bochum, Universitätsklinikum der Ruhr Universität Bochum, Bochum, Germany.
  • Schenk A; Institut für Diagnostische und Interventionelle Radiologie und Nuklearmedizin, Katholisches Klinikum Bochum, Universitätsklinikum der Ruhr Universität Bochum, Bochum, Germany.
Sci Rep ; 12(1): 12262, 2022 07 18.
Article em En | MEDLINE | ID: mdl-35851322
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Carcinoma Hepatocelular / Neoplasias Hepáticas Tipo de estudo: Prognostic_studies / Qualitative_research Limite: Humans Idioma: En 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: Carcinoma Hepatocelular / Neoplasias Hepáticas Tipo de estudo: Prognostic_studies / Qualitative_research Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article