Clustering algorithms support exploratory data analysis by grouping inputs that share similar features. Especially the clustering of unlabelled data is said to be a fiendishly difficult problem, because users not only have ...

Prostate cancer is one of the most prevalent cancers among males, and the use of magnetic resonance imaging (MRI) has been suggested for its detection. A framework is presented for scoring and visualizing various MR data ...

Maintaining both overview and detail while navigating in graphs, such as road networks, airline route maps, or social networks, is difficult, especially when targets of interest are located far apart. We present a navigation ...

High-dimensional data visualization is receiving increasing interest because of the growing abundance of highdimensional datasets. To understand such datasets, visualization of the structures present in the data, such as ...

We propose visual analytics techniques to support concurrent comparison of hundreds of cumulatively weighted instances of a single hierarchy. This includes a node-link representation of the hierarchy where nodes depict the ...

Until now a lot of visual analytics predominantly delivers qualitative results-based, for example, on a continuous color map or a detailed spatial encoding. Important target applications, however, such as medical diagnosis ...

High-dimensional data sets are a prevalent occurrence in many application domains. This data is commonly visualized using dimensionality reduction (DR) methods. DR methods provide e.g. a two-dimensional embedding of the ...

Scientific data acquired through sensors which monitor natural phenomena, as well as simulation data that imitate time-identified events, have fueled the need for interactive techniques to successfully analyze and understand ...

We introduce a novel approach for letting casual viewers explore detailed 3D models integrated with structured spatially associated descriptive information organized in a graph. Each node associates a subset of the 3D ...

Segmentation of volumetric data is an important part of many analysis pipelines, but frequently requires manual inspection and correction. While plenty of volume editing techniques exist, it remains cumbersome and errorprone ...