Visualization of DTI fibers using hair-rendering techniques

Diffusion Tensor Imaging (DTI) is an MRI technique that measures the diffusion of water in tissue such as white matter and muscle. From a DTI dataset, tracts representing fibers in the data can be reconstructed. Because of the vast amounts of fibers that can be reconstructed from a dataset, the visualization of these fibers is a challenging problem. In order to give the user a better understanding of the structure of the data, it is necessary to convey both the shapes of fibers, and the mutual coherency among multiple fibers and groups of fibers. Besides the fibers that were reconstructed, the local tensor properties, such as the second and third eigendirections and eigenvalues, are also of importance. We propose to use line illumination and shadowing of fibers in order to improve the perception of their structure. We also present a new method, inspired by the modeling of curled hair, for showing extra tensor properties along the fibers. This is done by showing curves that spirally wind around the actual fiber location, where the local tensor determines the parameters of that curve. We implemented the illumination, shadowing, and spiral curves, in such a way that the user can interact with the data and interactively change all parameters. The presented methods help in gaining more insight in DTI data of the brain and the heart. It is now possible to visualize more dense fiber structures using lighting and shadowing. The spiral curves help in evaluating the data where the extra tensor properties are of importance.