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This paper presents a new automatic technique for the segmentation of the rib cage on CT images. Motivated by a usage scenario in the context of large, heterogeneous databases of CT-images, we introduce two shape descriptors to be used in conjunction with a Random Forests (RF) classifier. These descriptors were specifically designed to address the challenges of rib identification under various acquisition...
In this paper a novel articulated atlas for the fully automated segmentation of the skeleton from head & neck CT datasets is presented. An individual atlas describing the shape and appearance is created for each individual bone. Principal Component Analysis is used to learn spatial relations between those atlases resulting in a unified articulated atlas. Transformations are parameterized using...
Statistical shape and intensity modelling have been subject to an increasing interest within the past decade. However, construction of such models requires large number of segmented examples. Accurate and automatic segmentation techniques that do not require any explicit prior model are therefore of high interest. We propose a fully-automatic method for segmenting the femur in 3D Computed Tomography...
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