Deep learning for fully-automatic quantification of avascular necrosis of the femoral head on 3D hip MRI in young patients eligible for joint preserving hip surgery: A pilot study

Ruckli, Adrian Cyrill; Schmaranzer, Florian; Lerch, Till; Boschung, Adam; Steppacher, Simon; Burger, Jürgen; Tannast, Moritz; Siebenrock, Klaus; Gerber, Kate; Gerber, Nicolas (17 May 2021). Deep learning for fully-automatic quantification of avascular necrosis of the femoral head on 3D hip MRI in young patients eligible for joint preserving hip surgery: A pilot study (Unpublished). In: Bern Data Science Day 2021. Bern. 23.04.2021. 10.5281/zenodo.4767398

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Item Type:

Conference or Workshop Item (Poster)

Division/Institute:

04 Faculty of Medicine > Faculty Institutions > sitem Center for Translational Medicine and Biomedical Entrepreneurship
04 Faculty of Medicine > Department of Orthopaedic, Plastic and Hand Surgery (DOPH) > Clinic of Orthopaedic Surgery
04 Faculty of Medicine > Department of Radiology, Neuroradiology and Nuclear Medicine (DRNN) > Institute of Diagnostic, Interventional and Paediatric Radiology
08 Faculty of Science > School of Biomedical and Precision Engineering (SBPE)
08 Faculty of Science > School of Biomedical and Precision Engineering (SBPE) > Personalised Medicine

Graduate School:

Graduate School for Cellular and Biomedical Sciences (GCB)

UniBE Contributor:

Ruckli, Adrian Cyrill, Schmaranzer, Florian, Lerch, Till, Steppacher, Simon Damian, Burger, Jürgen, Siebenrock, Klaus-Arno, Gerber, Kate, Gerber, Nicolas

Subjects:

600 Technology > 610 Medicine & health

Language:

English

Submitter:

Nicolas Gerber

Date Deposited:

13 Dec 2021 07:30

Last Modified:

24 Oct 2023 10:51

Publisher DOI:

10.5281/zenodo.4767398

Related URLs:

BORIS DOI:

10.48350/161489

URI:

https://boris.unibe.ch/id/eprint/161489

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