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This paper presents a comparison study between 10 automatic and six interactive methods for liver segmentation from contrast-enhanced CT images. It is based on results from the "MICCAI 2007 Grand Challenge" workshop, where 16 teams evaluated their algorithms on a common database. A collection of 20 clinical images with reference segmentations was provided(More)
The automatic segmentation of complex anatomical structures often fails due to low-contrast or missing edges, pathologic alterations , or high noise. As an alternative, we propose a novel two-stage semi-automatic algorithm that is able to segment complex structures like the liver shape with moderate user interaction. The first stage of our algorithm is the(More)
Probabilistic models are extensively used in medical image segmentation. Most of them employ parametric representations of densities and make idealizing assumptions, e.g., normal distribution of data. Often, such assumptions are inadequate and limit a broader application. We propose here a novel probabilistic active shape model for organ segmentation, which(More)
For the analysis of the brain shift phenomenon different strategies were applied. In 32 glioma cases pre- and intraoperative MR datasets were acquired in order to evaluate the maximum displacement of the brain surface and the deep tumor margin. After rigid registration using the software of the neuronavigation system, a direct comparison was made with 2D-(More)
The VOLCANO'09 Challenge invited participants to evaluate the change in size of pulmonary nodules in CT images; the challenge data set consisted of 50 pairs of CT scans each scan containing a single nodule. This is the first challenge for CAD methods on pulmonary nodules in which size change rather than volume estimation is the primary endpoint. Responses(More)
High performance deformation of volumetric objects is a common problem in computer graphics that has not yet been handled sufficiently. As a supplement to 3D texture based volume rendering, a novel approach is presented, which adaptively subdivides the volume into piecewise linear patches. An appropriate mathematical model based on tri-linear interpolation(More)
In this paper we introduce a new method for non-rigid voxel-based registration. In many medical applications there is a need to establish an alignment between two image datasets. Often a registration of a time-shifted medical image sequence with appearing deformation of soft tissue (e.g. pre-and intraoperative data) has to be conducted. Soft tissue(More)
Diffusion tensor imaging can be used to localize major white matter tracts within the human brain. For surgery of tumors near eloquent brain areas such as the pyramidal tract this information is of importance to achieve an optimal resection while avoiding post-operative neurological deficits. However, due to the small bandwidth of echo planar imaging,(More)
Reliable elasticity parameters describing the behavior of a given material are an important issue in the context of physically-based simulation. In this paper we introduce a method for the determination of the mechanical properties of brain tissue. Elasticity parameters Young's modulus E and Poisson's ratio nu are estimated in an iterative framework(More)