Title :
Strategies for direct volume rendering of diffusion tensor fields
Author :
Kindlmann, Gordon ; Weinstein, David ; Hart, David
Author_Institution :
Dept. of Comput. Sci., Utah Univ., Salt Lake City, UT, USA
Abstract :
Diffusion-weighted magnetic resonance imaging is a relatively new modality capable of elucidating the fibrous structure of certain types of tissue, such as the white matter within the brain. One tool for interpreting this data is volume rendering because it permits the visualization of three dimensional structure without a prior segmentation process. In order to use volume rendering, however, we must develop methods for assigning opacity and color to the data, and create a method to shade the data to improve the legibility of the rendering. Previous work introduced three such methods: barycentric opacity maps, hue-balls (for color), and lit-tensors (for shading). The paper expands on and generalizes these methods, describing and demonstrating further means of generating opacity, color, and shading from the tensor information. We also propose anisotropic reaction-diffusion volume textures as an additional tool for visualizing the structure of diffusion data. The patterns generated by this process can be visualized on their own or they can be used to supplement the volume rendering strategies described in the rest of the paper. Finally, because interpolation between data points is a fundamental issue in volume rendering, we conclude with a discussion and evaluation of three distinct interpolation methods suitable for diffusion tensor MRI data
Keywords :
colour graphics; image texture; interpolation; magnetic resonance imaging; rendering (computer graphics); tensors; anisotropic reaction-diffusion volume textures; barycentric opacity maps; color; data points; diffusion data; diffusion tensor MRI data; diffusion tensor fields; diffusion-weighted magnetic resonance imaging; direct volume rendering; hue-balls; interpolation methods; lit-tensors; opacity; tensor information; three dimensional structure; Anisotropic magnetoresistance; Data visualization; Eigenvalues and eigenfunctions; Ellipsoids; Image segmentation; Interpolation; Magnetic resonance imaging; Shape; Symmetric matrices; Tensile stress;
Journal_Title :
Visualization and Computer Graphics, IEEE Transactions on
DOI :
10.1109/2945.856994