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Automatic MRI-based Three-dimensional Models of Hip Cartilage Provide Improved Morphologic and Biochemical Analysis
Florian Schmaranzer1, Ronja Helfenstein, Guodong Zeng
1F. Schmaranzer, R. Helfenstein, T. D. Lerch, K. A. Siebenrock, M. Tannast, Department of Orthopaedic Surgery, Inselspital Bern, University of Bern, Switzerland, Bern, Switzerland G. Zeng, G. Zheng, Institute for Surgical Technology and Biomechanics, University of Bern, Switzerland, Bern, Switzerland F. Schmaranzer, E. N. Novais, J. D. Wylie, Y-J. Kim, Department of Orthopaedic Surgery, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
An automated deep learning method accurately analyzes hip cartilage composition and thickness using 3D delayed gadolinium-enhanced MRI of cartilage (dGEMRIC) scans. This approach is reliable, reproducible, and more time-efficient than manual methods, aiding surgical planning for hip conditions.
Failed At:
2026-06-19T13:47:34.187164+00:00
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