Principal Warps: Thin-Plate Splines and the Decomposition of Deformations
IEEE Transactions on Pattern Analysis and Machine Intelligence
SIGGRAPH '92 Proceedings of the 19th annual conference on Computer graphics and interactive techniques
Out-of-core simplification of large polygonal models
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
STACOM'10/CESC'10 Proceedings of the First international conference on Statistical atlases and computational models of the heart, and international conference on Cardiac electrophysiological simulation challenge
Personalization of cubic hermite meshes for efficient biomechanical simulations
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part II
The farthest point strategy for progressive image sampling
IEEE Transactions on Image Processing
STACOM'12 Proceedings of the third international conference on Statistical Atlases and Computational Models of the Heart: imaging and modelling challenges
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The analysis of large-scale simulation data from virtual populations can be effective to gain computational insight into disease mechanisms and treatment strategies, which can serve for generating hypotheses for and focusing subsequent clinical trials. This can be instrumental in shortening the critical path in medical product development and more cost-effective clinical trials. A previously published pipeline established point correspondence among volumetric meshes to enable meaningful statistics on cardiac electrophysiological simulations on the anatomical distribution of a large-scale virtual population. Thin Plate Splines (TPS), derived from surface deformations, were used to warp a template volumetric mesh, removing the costly operation of repeated volumetric meshing from the pipeline, but potentially at the cost of the volumetric mesh quality. In this work we compare (1) the influence of using TPS versus volumetric meshing of deformed surface meshes, and (2) the influence of surface mesh subsampling prior to the TPS computation. Our results suggest that warping of a template volumetric mesh introduces errors in electrophysiological simulation results of around 4 ms, while having computational times per mesh on the order of seconds, at surface subsampling rates of up to 80%.