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Image segmentation is one of the key problems in medical image analysis. This paper presents a new statistical shape model for automatic image segmentation. In contrast to the previous model based segmentation methods, where shape priors are estimated from a general population-based shape model, our proposed method aims to estimate patient-specific shape priors to achieve more accurate segmentation...
We propose a novel fully automatic three-label bone segmentation approach applied to knee segmentation (femur and tibia) from T1 and T2* magnetic resonance (MR) images. The three-label segmentation approach guarantees separate segmentations of femur and tibia which cannot be assured by general binary segmentation methods. The proposed approach is based on a convex optimization problem by embedding...
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...
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