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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)
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)
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)
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)
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)
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)
Intraoperative brain deformation (brain shift) induces a decrease in accuracy of neuronavigation systems during surgery. In order to compensate for occurring deformation of brain tissue, registration of time-shifted MR image sequences has to be conducted. In this paper we present a practical application of a novel approach for non-linear registration of(More)
OBJECTIVE In this paper we introduce a finite element-based strategy for simulation of brain deformation occurring during neurosurgery. The phenomenon, known as brain shift, causes a decrease in the accuracy of neuronavigation systems that rely on preoperatively acquired data. This can be compensated for with a computational model of the brain deformation(More)