669-04-012 ISMRM Abstract

User-independent AI-based MRI analysis of hepatobiliary function in patients with primary sclerosing cholangitis

Primary: Analysis Methods - Segmentation and Detection

Secondary: Body - Liver

669-04-012 · Twists and Turns: Pancreas, Cholangio, and Bowel MRI · Thursday, 14 May, 2:35 PM–3:30 PM · Digital Posters Row J

Keywords: Machine Learning/Artificial Intelligence Quantitative Imaging MRI Workflow optimzation Biomarker Contrast-enhancement

Accepted

Sina Dornbusch^1,2, Rebekka Fehling^1,2,3, Andrea Schenk^1,3, Eike Petersen^1,3, Felix Thielke³, Alena Levers¹, Henrike Lenzen^4,5, Frank Wacker¹, Kristina I Ringe¹

¹Department of Diagnostic and Interventional Radiology, Hannover Medical School, Hannover, Germany

²DigiStrucMed Program, Dean's Office for Academic Career Development, Hannover Medical School, Hannover, Germany

³Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany

⁴Department of Gastroenterology, Hepatology, Infectious Diseases and Endocrinology, Hannover Medical School, Hannover, Germany

⁵Department of Gastroenterology, Hepatology, Interventional Endoscopy and Diabetology, Municipal Hospital Braunschweig, Brunswick, Germany

Presenting Author: Daniel Düx

Synopsis

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References

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3. European Association for the Study of the Liver. EASL Clinical Practice Guidelines on sclerosing cholangitis. J Hepatol 2022 September 01;77(3):761–806. https://doi.org/10.1016/j.jhep.2022.05.011 PMID: 35738507 [doi] [pmid]

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