Deep learning for automatic quantification of AVN of the femoral head on 3D MRI in patients eligible for joint preserving surgery: A pilot study

Ruckli, Adrian Cyrill; Schmaranzer, F.; Lerch, T.; Boschung, A.; Steppacher, S.; Burger, Jürgen; Tannast, M.; Siebenrock, K.; Gerber, Nicolas; Gerber, Kate (4 June 2021). Deep learning for automatic quantification of AVN of the femoral head on 3D MRI in patients eligible for joint preserving surgery: A pilot study. International Journal of Computer Assisted Radiology and Surgery, 16(S1), S85-S86. Springer-Verlag

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Item Type:

 Conference or Workshop Item (Abstract)

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, Nicolas, Gerber, Kate

Subjects:

 600 Technology > 610 Medicine & health

ISSN:

 1861-6410

Publisher:

 Springer-Verlag

Language:

 English

Submitter:

 Nicolas Gerber

Date Deposited:

 06 Dec 2021 07:57

Last Modified:

 24 Oct 2023 10:52

Related URLs:

BORIS DOI:

 10.48350/161449

URI:

 https://boris.unibe.ch/id/eprint/161449

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