Effectiveness of a state-of-the-art neural network for liver parenchyma, portal and hepatic vein segmentation based on a standard non-contrast T1-vibe Dixon sequence

Zbinden, Lukas; Catucci, D; Suter, Yannick Raphael; Berzigotti, Annalisa; Ebner, Lukas; Christe, Andreas; Obmann, Verena Carola; Sznitman, Raphael; Huber, Adrian Thomas (May 2022). Effectiveness of a state-of-the-art neural network for liver parenchyma, portal and hepatic vein segmentation based on a standard non-contrast T1-vibe Dixon sequence (Unpublished). In: ESGAR 2022. Lisbon. May 2022.

Official URL: https://www.esgar.org/

Item Type:

 Conference or Workshop Item (Abstract)

Division/Institute:

 10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research
04 Faculty of Medicine > Department of Radiology, Neuroradiology and Nuclear Medicine (DRNN) > Institute of Diagnostic, Interventional and Paediatric Radiology
10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research > ARTORG Center - AI in Medical Imaging Laboratory
04 Faculty of Medicine > Department of Gastro-intestinal, Liver and Lung Disorders (DMLL) > Clinic of Visceral Surgery and Medicine > Hepatology

UniBE Contributor:

 Zbinden, Lukas, Suter, Yannick Raphael, Berzigotti, Annalisa, Ebner, Lukas, Christe, Andreas, Obmann, Verena Carola, Sznitman, Raphael, Huber, Adrian Thomas

Subjects:

 500 Science > 570 Life sciences; biology
600 Technology > 610 Medicine & health

Language:

 English

Submitter:

 Maria de Fatima Henriques Bernardo

Date Deposited:

 10 Jun 2022 15:28

Last Modified:

 05 Dec 2022 16:20

Additional Information:

Oral scientific presentation

URI:

 https://boris.unibe.ch/id/eprint/170571

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