Jörg-Stefan Praßni

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In this paper we describe an interactive labeling algorithm, which allows to integrate internal 3D labels into medical visualizations generated from volumetric data sets. The proposed algorithm is motivated by internal labeling techniques found in anatomical atlases, and in contrast to existing algorithms it provides additional shape cues by fitting(More)
Although direct volume rendering is established as a powerful tool for the visualization of volumetric data, efficient and reliable feature detection is still an open topic. Usually, a tradeoff between fast but imprecise classification schemes and accurate but time-consuming segmentation techniques has to be made. Furthermore, the issue of uncertainty(More)
In this paper we propose an algorithm for combining multiple image segmentations to achieve a final improved segmentation. In contrast to previous works we consider the most general class of segmentation combination , i.e. each input segmentation has an arbitrary number of regions. Our approach is based on a random walker segmentation algorithm which is(More)
We present concepts for pre-operative planning of brain tumor resections. The proposed system uses a combination of traditional and novel visualization techniques rendered in real-time on modern GPUs in order to support neu-rosurgeons during intervention planning. A set of multimodal 2D and 3D renderings conveys the relation between the lesion and the(More)
We present a novel classification technique for volume visualization that takes the shape of volumetric features into account. The presented technique enables the user to distinguish features based on their 3D shape and to assign individual optical properties to these. Based on a rough pre-segmentation that can be done by window-ing, we exploit the(More)
In this paper we present an efficient technique for the construction of LH histograms which, in contrast to previous work, does not require an expensive tracking of intensity profiles across boundaries and therefore allows an LH classification in real time. We propose a volume exploration system for the semi-automatic generation of LH transfer functions,(More)
Background: Visualization of multi-channel microscopy data plays a vital role in biological research. With the ever-increasing resolution of modern microscopes the data set size of the scanned specimen grows steadily. On commodity hardware this size easily exceeds the available main memory and the even more limited GPU memory. Common volume rendering(More)
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