Papers on Simulation

High-Resolution Interaction with Corotational Coarsening Models ACM SIGGRAPH conference and exhibition on computer graphics and interactive techniques in Asia 2016

Abstract.
This paper presents a numerical coarsening method for corotational elasticity, which enables interactive large deformation of high-resolution heterogeneous objects. Our method derives a coarse elastic model from a high-resolution discretization of corotational elasticity with high-resolution boundary conditions. This is in contrast to previous coarsening methods, which derive a coarse elastic model from an unconstrained high-resolution discretization of regular linear elasticity, and then apply corotational computations directly on the coarse setting. We show that previous approaches fail to handle high-resolution boundary conditions correctly, suffering accuracy and robustness problems. Our method, on the other hand, supports efficiently accurate high-resolution boundary conditions, which are fundamental for rich interaction with high-resolution heterogeneous models. We demonstrate the potential of our method for interactive deformation of complex medical imaging data sets.

Paper avaliable at High-Resolution Interaction of Volume Data

Interactive Deformation of Heterogeneous Volume Data, ACCEPTED in ISBMS 2014

Abstract.
This paper presents a method to interactively deform volume
images with heterogeneous structural content, using coarse tetrahedral
meshes. It rests on two major components: a massively parallel
algorithm for the rasterization of tetrahedral meshes, and a method to
define a coarse deformable tetrahedral mesh from the homogenization
of a fine heterogeneous mesh. We show the potential of the method for
training and planning applications through two examples: an abdominal
CT exploration and the alignment of breast CT and MRIs.

Paper avaliable at Deformation of Volume Data

Fast Deformation of Volume Data Using Tetrahedral Mesh Rasterization, ACCEPTED in SCA 2013

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 high-resolution 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.

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