Titlebook: Visualization in Medicine and Life Sciences III; Towards Making an Im Lars Linsen,Bernd Hamann,Hans-Christian Hege Conference proceedings 2

怒目而視

Multi-Modal Visualization of Probabilistic Tractographyities. First, we provide an overview of the currently used visualization techniques. Then, we show how probabilistic tractography can be combined with other techniques, trying to find new and useful visualizations for multi-modal data.

成績(jī)上升

尊敬

Combined Volume Registration and Visualizationmulated annealing algorithm to find a registration close to optimal and allow the user to closely monitor the optimization progress. The combined calculation reduces memory traffic, increases rendering frame rate, and makes possible interactive-speed, user-supervised, semi-automatic combination of many component volumetric data sets.

拖網(wǎng)

DUCE

Fast Uncertainty-Guided Fuzzy C-Means Segmentation of Medical Imagess segmentation of MRI data. The algorithm consists of two steps, which are executed as two iterations of a fuzzy c-means approach: the first iteration is a standard fuzzy c-means (FCM) iteration, while the second iteration is our modified FCM iteration with misclassification correction. In the secon

Apoptosis

muView: A Visual Analysis System for Exploring Uncertainty in Myocardial Ischemia Simulationsia. The simulation uses a collection of conductivity values to understand how ischemic regions effect the undamaged anisotropic heart tissue. The data resulting from the simulation is multi-valued and volumetric, and thus, for every data point, we have a collection of samples describing cardiac elec

Communal

勉強(qiáng)

諷刺

Remote Visualization Techniques for Medical Imaging Research and Image-Guided Procedureseed, driven by the sheer amount of multimodal medical image data but also by the broad spectrum of computer-assisted applications. At the same time, user expectations with respect to diagnostic accuracy, robustness, speed, automation, workflow efficiency, broad availability, as well as intuitive use

ODIUM

Visualization of MRI Diffusion Data by a Multi-Kernel LIC Approach with Anisotropic Glyph Samplesion profile to be measured and represented with high fidelity by a fiber orientation distribution function (FOD), even in situations of crossing and branching white matter fibers. Fiber tractography algorithms, such as streamline tracking, are used for visualizing global relationships between brain