Combined image processing techniques for characterization of MRI cartilage of the knee

A common manifestation of osteoarthritis (OA) of the knee is the morphological degeneration of articular cartilage. In vivo magnetic resonance imaging (MRI) offers the potential to visualize and analyze quantitatively morphology such as cartilage thickness and volume. The purpose of this work was the development of new image processing techniques and application of existing ones for the intra and inter-subject quantitative analysis of cartilage of the knee. The process consists of MRI acquisition, cartilage segmentation, shape-based interpolation of segmented cartilage, segmentation of bone, volume registration based on bone structures, analysis, and visualization. The process is semi-automatic, the segmentation which is based on Bezier splines and edge detection requires interaction. Different shape interpolation methods were compared. The registration is based on shape matching and can be rigid-body and elastic. The analysis comprises cartilage volume and thickness calculations. The visualization allows the depiction of cartilage thickness maps overlaid on MR images or in three dimensions (3D). The cartilage segmentation and shape-based interpolation techniques were validated visually and based on the volumetric measurements of images of porcine knees which cartilage volume were directly measured using a saline displacement method. The registration technique was validated visually and using manual landmark registration.