Advancing deep learning based knee cartilage segmentation in MRI: Innovations, challenges and applications
DL-based segmentation is advancing musculoskeletal imaging by offering reliable and automated solutions. Despite persistent challenges such as data scarcity, domain shifts, and imaging variability, advancements in areas like semi-supervised learning, domain adaptation, augmentation strategies, and foundation models present significant opportunities to enhance model robustness and expand clinical applicability.
Authors
- Muhammad Muneeb Asim (ORCID: https://orcid.org/0000-0003-2145-4880)
- Weitian Chen (ORCID: https://orcid.org/0000-0001-7242-9285)
- Sheheryar Khan (ORCID: https://orcid.org/0000-0002-1975-4334)
- Rizwan Qureshi (ORCID: https://orcid.org/0000-0002-0039-982X)
- Junru Zhong (ORCID: https://orcid.org/0000-0002-3897-9280)
- Muhammad Ammar Khawer
Institutions
- University of Central Florida (US)
- Hong Kong Polytechnic University (HK)
- Chinese University of Hong Kong (HK)
Publication Details
- Journal
- Osteoarthritis and Cartilage Open
- Published
- 2025-11-15
- DOI
- https://doi.org/10.1016/j.ocarto.2025.100702
- Citations
- 1
- Primary Topic
- Osteoarthritis Treatment and Mechanisms
- Type
- article
- Field-Weighted Citation Impact
- 1.67