A new composite model of objects for Monte Carlo simulation of radiological imaging.
A composite object model is proposed for Monte Carlo simulation of radiological imaging systems. The composite model contains four components: a set of regular and 'voxelized' primitives, a 'modular' inclusion tree, a set of designated constructive solid geometry (CSG) trees, and a mapping from the set of CSG trees to the inclusion tree. The voxelized primitive is a primitive containing a stack of voxels whose intersections with a photon path are calculated based on Siddon's method. The inclusion tree is employed to describe the inclusion relationships of homogeneous subregions of material characteristics in larger regions in an object. The model is designed so that the 'divide-and-conquer' principle for modular software design can be used to construct an inclusion tree for a complex object. The designated CSG trees are used to model source distributions. The mapping from the inclusion tree to the CSG trees provides the fundamental information for the initial location of a photon history in the tree. Computational issues are addressed for the new model. For the modular inclusion tree, a computationally efficient algorithm is proposed in conjunction with the determination of the photon-ray intersections with primitive and voxel boundaries as well as with the identification of the material characteristics for each ray segment between two adjacent intersections. For source distributions, the designated CSG trees are defined based on the set intersections-difference-unions (IDU) operation sequence. The IDU operations present computation advantages over existing source modelling based on a single inclusion tree. For voxelized primitives, a new sampling technique called the fractional photon emission technique is introduced to reduce sampling computations for existing techniques based on single photon emission. The composite model is an extension of existing simple-geometry, solid-geometry, and voxel-based models and hence provides greater flexibility for model optimization. Based on the composite model, two objects were simulated: an anthropomorphic thorax with lesion inserts for transmission studies and a 3D Hoffman brain phantom with lesion inserts for emission studies. The simulations demonstrate the flexibility of the composite approach in modelling objects for clinically significant applications.
Wang
H
H
Department of Radiology, Duke University Medical Center, Durham, NC 27710.
Jaszczak
R J
RJ
Coleman
R E
RE
D003198:Computer Simulation; D003952:Diagnostic Imaging; D006801:Humans; D008961:Models, Structural; D009010:Monte Carlo Method