Visual analysis of 3D diffusion tensor fields has become an important topic especially in medical imaging for understanding
microscopic structures and physical properties of biological tissues. However, it is still difficult to continuously track the
underlying features from discrete tensor samples, due to the absence of appropriate interpolation schemes in the sense
that we are able to handle possible degeneracy while fully respecting the smooth transition of tensor anisotropic features.
This is because the degeneracy may cause rotational inconsistency of tensor anisotropy. This paper presents such an
approach to interpolating 3D diffusion tensor fields. The primary idea behind our approach is to resolve the possible
degeneracy through optimizing the rotational transformation between a pair of neighboring tensors by analyzing their
associated eigenstructure, while the degeneracy can be identified by applying a minimum spanning tree-based clustering
algorithm to the original tensor samples. Comparisons with existing interpolation schemes will be provided to demonstrate
the advantages of our scheme, together with several results of tracking white matter fiber bundles in a human brain.
The Interval Volume Decomposer (IVD) is an interface for decomposing an entire volume into interval volumes each of which characterizes a distinctive volume feature. The advantage of the IVD is that it allows us to look inside the volume by peeling interval volumes from outside to inside not only interactively but also automatically. This is achieved due to the rigorous analysis of nested structures of the decomposed interval volumes by constructing a level-set graph that delineates isosurface transitions according to the scalar field. A robust algorithm for computing such level-set graphs is introduced in order to extract significant structures in the volume by putting together local interval volumes into a finite number of
global groups. Several decomposition examples of medical and simulated datasets are demonstrated so that the present interface effectively traverses the underlying structures of the volume.
Conference Committee Involvement (3)
Visualization and Data Analysis 2015
9 February 2015 | San Francisco, California, United States
Visualization and Data Analysis 2014
3 February 2014 | San Francisco, California, United States
Visualization and Data Analysis 2013
4 February 2013 | Burlingame, California, United States