Background: Osteoarthritis (OA) is a degenerative disease of joint cartilage affecting the elderly people around the world. Visualization and quantification of cartilage is very much essential for the assessment of OA and rehabilitation of the affected people. Magnetic Resonance Imaging (MRI) is the most widely used imaging modality in the treatment of knee joint diseases. But there are many challenges in proper visualization and quantification of articular cartilage using MRI. Volume rendering and 3D visualization can provide an overview of anatomy and disease condition of knee joint. In this work, cartilage is segmented from knee joint MRI, visualized in 3D using Volume of Interest (VOI) approach. Methods: Visualization of cartilage helps in the assessment of cartilage degradation in diseased knee joints. Cartilage thickness and volume were quantified using image processing techniques in OA affected knee joints. Statistical analysis is carried out on processed data set consisting of 110 of knee joints which include male (56) and female (54) of normal (22) and different stages of OA (88). The differences in thickness and volume of cartilage were observed in cartilage in groups based on age, gender and BMI in normal and progressive OA knee joints. Results: The results show that size and volume of cartilage are found to be significantly low in OA as compared to normal knee joints. The cartilage thickness and volume is significantly low for people with age 50 years and above and Body Mass Index (BMI) equal and greater than 25. Cartilage volume correlates with the progression of the disease and can be used for the evaluation of the response to therapies. Conclusion: The developed methods can be used as helping tool in the assessment of cartilage degradation in OA affected knee joint patients and treatment planning.

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Knee is a complex and articulated joint of the body. Cartilage is a smooth hyaline spongy material between the tibia and femur bones of knee joint. Cartilage morphology change is an important biomarker for the progression of osteoarthritis (OA). Magnetic resonance imaging (MRI) is the modality widely used to image the knee joint because of its hazard free and high resolution soft tissue contrast. Cartilage thickness measurement and visualization is useful for early detection and progression of the disease in case of OA affected patients. A wide variety of algorithms are available for knee joint image segmentation. They are classified as pixel based and model based methods. Based on the human intervention required, segmentation methods are also classified as manual, semi-automatic and fully automatic methods. This paper reviews knee joint articular cartilage segmentation methods, visualization, thickness measurement, volume measurement and validation methods.

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