Hybrid phantom representation for simulation of CT systems using intrinsic shapes, tomographic volumes and higher-order surfaces

We have extended our previously introduced hybrid phantom model to allow for phantom representation by higher-order surfaces (point meshes, polygonal meshes) in addition to any combination of intrinsic shapes (cubes, quadrics, super-quadrics) and voxel data originating from tomography (segmented CT/MRI volumes). Higher-order surfaces can be represented by uniform and non-uniform triangles obtained by means of Delaunay's algorithm. In order to optimize computational performance for intersection calculations, a variety of efficient rejection tests has been introduced and a novel numerical algorithm which relies on a strategy similar to cue optimization is proposed. The proposed phantom model allows for unlimited complexity and number of phantom compartments. Various hybrid phantom representation examples including associated Monte Carlo simulation studies are presented and demonstrate the enormous versatility of our simulation framework. Compared to previous implementations computational speed has improved for simulation of PET and SPECT systems by more than 40% on the same workstation with the same hardware.