Fast Deformation of Volume Data Using Tetrahedral Mesh Rasterization

Abstract

Many inherently deformable structures, such as human anatomy, are often represented using a regular volumetric discretization, e.g., in medical imaging. While deformation algorithms employ discretizations that deform themselves along with the material, visualization algorithms are optimized for regular undeformed discretizations. In this paper, we propose a method to transform highresolution volume data embedded in a deformable tetrahedral mesh. We cast volume deformation as a problem of tetrahedral rasterization with 3D texture mapping. Then, the core of our solution to volume data deformation is a very fast algorithm for tetrahedral rasterization. We perform rasterization as a massively parallel operation on target voxels, and we minimize the number of voxels to be handled using a multi-resolution culling approach. Our method allows the deformation of volume data with over 20 million voxels at interactive rates.