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In this paper, we present a segmentation scheme that automatically and accurately segments all the cartilages from magnetic resonance (MR) images of nonpathological knees. Our scheme involves the automatic segmentation of the bones using a three-dimensional active shape model, the extraction of the expected bone-cartilage interface (BCI), and cartilage segmentation from the BCI using a deformable...
Pathologic processes active in early-stage knee joint osteoarthritis may also affect the integrity of the crescent-shaped fibrocartilagenous structures called menisci. Magnetic resonance imaging can allow the detection of these structural changes, however, large-scale clinical application remains limited by tedious and labor-intensive techniques for volumetric measurement. Towards automating these...
We present and validate a hybrid segmentation scheme based around 3D active shape models, which is used to automatically segment the three bones in the knee joint. This scheme is automatically initialised using an affine registration to an atlas. The accuracy and robustness of the approach was experimentally validated using an MR database of 20 fat suppressed spoiled gradient recall images. A median...
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