An automated technique to estimate knee cartilage thickness for femoral, tibial, patellar cartilages and menisci

作者：Deepthi Sundaran, Laura Gomez, Bruno Nunes, Jignesh Dholakia, Maggie Fung · 发表于：Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition · 年份：2025 · DOI：10.58530/2025/2954 · 被引用次数：1 · 研究领域：Osteoarthritis Treatment and Mechanisms、Lower Extremity Biomechanics and Pathologies、Total Knee Arthroplasty Outcomes

Motivation: Accurate estimation of knee cartilage thickness is crucial for assessing cartilage health and tracking disease progression, such as in osteoarthritis. Goal(s): To propose a generic, non-DL algorithm that estimates the thickness of three cartilage compartments —femur, tibia, patella —and the meniscus, allowing visualization in 2D/3D. Approach: The method involves isolating bone and cartilage surfaces from pre-segmented volumes using selected morphological processes. Thickness is then calculated with a nearest neighbor algorithm and encoded onto one surface to enable visualization. Results: Accuracy is evaluated using digital phantoms and validated by comparison with manual measurements from clinical experts. Impact: Cartilage thickness estimation holds significant clinical value and the proposed method enables efficient thickness estimation and visualization of all cartilage compartments - femur, tibia, patella and meniscus in a generic and less computationally intensive manner.