Probabilistic segmentation algorithms compute for each voxel and each segment of a medical imaging data set a probability that the voxel belongs to the segment. These per-voxel probability vectors are commonly used to ...

Visualizing the deformation of the myocardium over an entire heart cycle is essential for the assessment of local defects in the heart muscle. For this purpose, an automatic segmentation of the myocardium is a key requirement, ...

DNA microarray technology has enabled researchers to simultaneously investigate thousands of genes over hundreds of samples. Automatic classification of such data faces the challenge of dealing with smaller number of samples ...

Dynamical processes on networks play an important role in systems biology and statistical physics. To understand these processes, it is essential to understand which topological properties of the network are the main factors ...

Projection methods support effective visualizations of multidimensional data. Linear projections are an importantsubclass, as they allow for interactive visual exploration of the data space and feature sensitivity analysis. ...

Interactive visual analysis of volumetric data relies on intuitive, yet powerful mechanisms to generate transfer functions. For multi-variate data, traditional methods for interactive transfer functions generation are of ...

Stenosis refers to the thinning of the inner surface (lumen) of vascular structures. Detecting stenoses and correctly estimating their degree is crucial in clinical settings for proper treatment planning. Such a planning ...

Magnetic Resonance Spectroscopy Imaging (MRSI) is an in-vivo method for measuring metabolite concentration in various tissues. Typically, individual metabolites are examined in detail. We provide an interactive visualization ...

The role of network topology on the dynamics in simulations that are executed on the network is a central question in the field of network science. However, the influence of the topology is affected by the global dynamical ...

Investigating etiology of a disease depends on the combination of tacit medical knowledge and multivariate analysis on a wide array of collected data. Confounding variables may generate a bias when exploring disease ...