Comparative and ensemble visualization of diffusion tensor fields

Comparative and ensemble visualization of diffusion tensor fields

Zhang, C. (TU Delft Computer Graphics and Visualisation)

Eisemann, E. (promotor)
Vilanova Bartroli, A. (copromotor)

Delft University of Technology

2017-12-12

Scientific visualization of tensor fields is challenging due to the complex and multivariate nature of tensor data. The visualization of multiple tensor fields becomes even more difficult, and still in its infancy. This thesis aims at contributing visual analysis techniques for multiple 3D tensor fields.
We focus specifically on the visual analysis of Diffusion Tensor Imaging (DTI)
datasets. DTI is a magnetic resonance imaging (MRI) based modality, which is commonly used in neuroscience to investigate brain white matter in vivo. It requires a long scanning time compared to other imaging modalities. Acceleration of MRI acquisitions has the potential to improve the applicability of DTI. Compressed sensing (CS) is a signal reconstruction technique that is used to accelerate MRI acquisitions. The traditional CS method aims at optimizing the global quality of the reconstructed image.
However, in practice, the quality of local structures is often of more interest. Therefore, we investigate CS for this purpose and contribute in this direction by adapting the traditional CS reconstruction method to focus on the quality of local structures.

Diffusion Tensor Fields
Comparative Visualization
Ensemble Visualization
Glyph Design
Visual Analysis

https://doi.org/10.4233/uuid:5b0da969-6e43-4cfa-bd33-09494ecfe199

978-94-92516-96-1

Institutional Repository

doctoral thesis

© 2017 C. Zhang