MRI-derived quantification of hepatic vessel-to-volume ratios in chronic liver disease using a deep learning approach.
Saved in:
| Title: | MRI-derived quantification of hepatic vessel-to-volume ratios in chronic liver disease using a deep learning approach. |
|---|---|
| Authors: | Herold A; Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria., Sobotka D; Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria., Beer L; Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria., Bastati N; Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria., Poetter-Lang S; Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria., Weber M; Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria., Reiberger T; Division of Gastroenterology and Hepatology, Department of Medicine III, Medical University of Vienna, Vienna, Austria.; Vienna Hepatic Hemodynamic Lab, Division of Gastroenterology and Hepatology, Department of Medicine III, Medical University of Vienna, Vienna, Austria.; Christian Doppler Laboratory for Portal Hypertension and Liver Fibrosis, Medical University of Vienna, Vienna, Austria.; Clinical Research Group MOTION, Medical University of Vienna, Vienna, Austria., Mandorfer M; Division of Gastroenterology and Hepatology, Department of Medicine III, Medical University of Vienna, Vienna, Austria.; Vienna Hepatic Hemodynamic Lab, Division of Gastroenterology and Hepatology, Department of Medicine III, Medical University of Vienna, Vienna, Austria.; Clinical Research Group MOTION, Medical University of Vienna, Vienna, Austria., Semmler G; Division of Gastroenterology and Hepatology, Department of Medicine III, Medical University of Vienna, Vienna, Austria.; Vienna Hepatic Hemodynamic Lab, Division of Gastroenterology and Hepatology, Department of Medicine III, Medical University of Vienna, Vienna, Austria.; Clinical Research Group MOTION, Medical University of Vienna, Vienna, Austria., Simbrunner B; Division of Gastroenterology and Hepatology, Department of Medicine III, Medical University of Vienna, Vienna, Austria.; Vienna Hepatic Hemodynamic Lab, Division of Gastroenterology and Hepatology, Department of Medicine III, Medical University of Vienna, Vienna, Austria.; Christian Doppler Laboratory for Portal Hypertension and Liver Fibrosis, Medical University of Vienna, Vienna, Austria.; Clinical Research Group MOTION, Medical University of Vienna, Vienna, Austria., Wichtmann BD; Department of Neuroradiology, University Hospital Bonn, Bonn, Germany., Ba-Ssalamah SA; Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria., Trauner M; Division of Gastroenterology and Hepatology, Department of Medicine III, Medical University of Vienna, Vienna, Austria.; Clinical Research Group MOTION, Medical University of Vienna, Vienna, Austria., Ba-Ssalamah A; Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria. ahmed.ba-ssalamah@meduniwien.ac.at., Langs G; Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria.; Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria. |
| Source: | European radiology experimental [Eur Radiol Exp] 2025 Aug 12; Vol. 9 (1), pp. 75. Date of Electronic Publication: 2025 Aug 12. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: SpringerOpen Country of Publication: England NLM ID: 101721752 Publication Model: Electronic Cited Medium: Internet ISSN: 2509-9280 (Electronic) Linking ISSN: 25099280 NLM ISO Abbreviation: Eur Radiol Exp Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
|
Full text is not displayed to guests.
Login for full access.
|
|
Be the first to leave a comment!
