| dc.contributor.author | Muraki, S. | en_US |
| dc.contributor.author | Fujishiro, I. | en_US |
| dc.contributor.author | Suzuki, Y. | en_US |
| dc.contributor.author | Takeshima, Y. | en_US |
| dc.contributor.editor | Raghu Machiraju and Torsten Moeller | en_US |
| dc.date.accessioned | 2014-01-29T17:50:01Z | |
| dc.date.available | 2014-01-29T17:50:01Z | |
| dc.date.issued | 2006 | en_US |
| dc.identifier.isbn | 3-905673-41-X | en_US |
| dc.identifier.issn | 1727-8376 | en_US |
| dc.identifier.uri | http://dx.doi.org/10.2312/VG/VG06/119-126 | en_US |
| dc.description.abstract | In this paper, we present a novel method, called diffusion-based tractography (DBT), for visualizing diffusion tensor magnetic resonance imaging datasets. The DBT method generates 3D textures similar to the line integral convolution (LIC) by smearing 3D random dot textures. In contrast to the LIC method, which only traces a single direction, the DBT method takes into account both linear and planar diffusion components, and suppresses excessive blur by an analysis of three decomposed components. We will demonstrate that the DBT method is effective for visualizing dense white matter connectivity from 3D diffusion tensor fields and that it is suitable for hardware acceleration using commodity graphics processors. | en_US |
| dc.publisher | The Eurographics Association | en_US |
| dc.subject | Categories and Subject Descriptors (according to ACM CCS): I.3.3 [Computer Graphics]: Line and Curve Generation I.3.8 [Computer Graphics]: Applications I.6.8 [Simulation and Modeling]: Visual | en_US |
| dc.title | Diffusion-Based Tractography: Visualizing Dense White Matter Connectivity from 3D Tensor Fields | en_US |
| dc.description.seriesinformation | Volume Graphics | en_US |
