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We propose an automatic procedure for the correct segmen-tation of grey and white matter in MR data sets of the human brain. Our method exploits general anatomical knowledge for the initial segmenta-tion and for the subsequent refinement of the estimation of the cortical grey matter. Our results are comparable to manual segmentations.
We propose an algorithm for the segmentation of blood vessels in the kind of CT-data typical for diagnostics in a clinical environment. Due to poor quality and variance in the properties of the data sets a two level approach using implicit active contours is chosen for the task. A fast pre-segmentation using the fast marching method followed by propagation(More)
Level set methods are a well-known means for the segmentation of objects in image data. In this paper, we discuss a class of easy to calculate terms based on distance measures for integration into the level set speed function. We will give examples for the use of these distance-based terms as a stopping criterion in the absence of reliable image features(More)
The paper focusses on a group of segmentation problems dealing with 3D data sets showing thin objects that appear disconnected in the data due to partial volume effects or a large spacing between neighbouring slices. We propose a modification of the speed function for the well-known level set method to bridge these discontinuities. This allows for the(More)
Level set methods have become very popular means for image segmentation in recent years. But due to the data-driven nature of this methods it is difficult to segment objects that appear unconnected within the data. We propose a modification of the level set speed function to add a " bridging force " that allows the level set to leap over gaps in the data(More)
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