Stochastic Neighbor Embedding for interactive visualization of flow patterns in 4D flow MRI

Flow visualization is an important topic in many scientific domains and has been an active field of research for many years. Many different methods of analysis can be used in order to analyze flow, however recently big progress have been reported on the manifold learning algorithms for high-dimensional data. This thesis investigates the use of...

Interactive Visual Exploration of 3D Mass Spectrometry Imaging Data Using Hierarchical Stochastic Neighbor Embedding Reveals Spatiomolecular Structures at Full Data Resolution

Technological advances in mass spectrometry imaging (MSI) have contributed to growing interest in 3D MSI. However, the large size of 3D MSI data sets has made their efficient analysis and visualization and the identification of informative molecular patterns computationally challenging. Hierarchical stochastic neighbor embedding (HSNE), a...