1 research outputs found
Voxlines: Streamline Transparency through Voxelization and View-Dependent Line Orders
As tractography datasets continue to grow in size, there is a need for
improved visualization methods that can capture structural patterns occurring
in large tractography datasets. Transparency is an increasingly important
aspect of finding these patterns in large datasets but is inaccessible to
tractography due to performance limitations. In this paper, we propose a
rendering method that achieves performant rendering of transparent streamlines,
allowing for exploration of deeper brain structures interactively. The method
achieves this through a novel approximate order-independent transparency method
that utilizes voxelization and caching view-dependent line orders per voxel. We
compare our transparency method with existing tractography visualization
software in terms of performance and the ability to capture deeper structures
in the dataset.Comment: 12 pages. 4 figures. Accepted at Computational Diffusion MRI Workshop
(CDMRI) at Medical Image Computing and Computer Assisted Intervention
(MICCAI) 202