Andre Reichenbach

TL;DR: This paper focuses on the thermal noise that is present in all MRI measurements and compares its effect on the output of several established tractography algorithms, and indicates that among the algorithms tested, the Tensorlines approach is the most robust for tracking white matter fiber bundles and both theTensorlines and the Bayes DTI approach are good choices for calculating gray matter structural connectivity.

TL;DR: This work proposes an interactive illustrative 3D visualization for both structural connectivity data and cortex parcellations in anatomical space and employs interactivity and illustrative depth-enhancing, which help the user to build a mental map of the connections in the brain.

TL;DR: This work presents an illustrative technique for probabilistic tracts in such configurations, which is based on Fiber-Stippling and supports multiple diffusion directions as given by high angular resolution diffusion images (HARDI) and hence can visualize crossing tracts, while preserving all of the advantages of Fiber- Stippling.

TL;DR: This work suggests a visualization based on Fiber-Stippling but sensible to multiple diffusion orientations from HARDI-based diffusion models, which implies that tract crossings may now be visualized as crossing stipples, which is an essential step towards an accurate visualization of the neuroanatomy.