Quantification of Articular Cartilage from MR Images Using Active Shape Models
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume II - Volume II
Image Registration Using Hierarchical B-Splines
IEEE Transactions on Visualization and Computer Graphics
Automatic segmentation of articular cartilage in magnetic resonance images of the knee
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention
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We present a new approach for quantifying the degradation of knee cartilage in the medial meniscal tear (MMT) model of osteoarthritis in the rat. A statistical strategy was used to guide the selection of a region of interest (ROI) from the images obtained from a pilot study. We hypothesize that this strategy can be used to localize a region of cartilage most vulnerable to MMT-induced damage. In order to test this hypothesis, a longitudinal study was conducted in which knee cartilage thickness in a pre-selected ROI was monitored for three weeks and comparisons were made between MMT and control rats. We observed a significant decrease in cartilage thickness in MMT rats and a significant increase in cartilage thickness in sham-operated rats as early as one week post surgery when compared to pre-surgery measurements.