Automated liver lesion detection in <sup>68</sup>Ga DOTATATE PET/CT using a deep fully convolutional neural network.

Wehrend, Jonathan; Silosky, Michael; Xing, Fuyong; Chin, Bennett B

Automated liver lesion detection in ⁶⁸Ga DOTATATE PET/CT using a deep fully convolutional neural network.

Wehrend, Jonathan; Silosky, Michael; Xing, Fuyong; Chin, Bennett B.

Afiliação

Wehrend J; Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, University of Colorado School of Medicine Anschutz Medical Campus, 12401 East 17th Avenue, Mail Stop L954A, Aurora, CO, 80045, USA.
Silosky M; Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, University of Colorado School of Medicine Anschutz Medical Campus, 12401 East 17th Avenue, Mail Stop L954A, Aurora, CO, 80045, USA.
Xing F; Department of Biostatistics and Informatics Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
Chin BB; Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, University of Colorado School of Medicine Anschutz Medical Campus, 12401 East 17th Avenue, Mail Stop L954A, Aurora, CO, 80045, USA. bennett.chin@cuanschutz.edu.

EJNMMI Res ; 11(1): 98, 2021 Oct 02.

Article em En | MEDLINE | ID: mdl-34601660

Palavras-chave

Convolutional neural network; DOTATATE; Deep learning; Liver tumor; Neuroendocrine tumor; Positron emission tomography; Somatostatin receptor

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: EJNMMI Res Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos

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