Papers › FastCAT: Fast Cone Beam CT (CBCT) Simulation
FastCAT: Fast Cone Beam CT (CBCT) Simulation
Jericho O'Connell, Magdalena Bazalova-Carter
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The fastCAT application uses pre-calculated Monte Carlo (MC) CBCT phantom-specific scatter and detector response functions to reduce simulation time for megavoltage (MV) and kilovoltage (kV) CBCT imaging. Pre-calculated x-ray beam energy spectra, detector optical spread functions and energy deposition, and phantom scatter kernels are combined with GPU raytracing to produce CBCT volumes. MV x-ray beam spectra are simulated with EGSnrc for 2.5 and 6 MeV electron beams incident on a variety of target materials and kV x-ray beam spectra are calculated analytically for an x-ray tube with a tungsten anode. Detectors were modelled in Geant4 extended by Topas and included optical transport in the scintillators. Two MV detectors were modelled, a standard Varian AS1200 GOS detector and a novel CWO high detective quantum efficiency detector. A kV CsI detector was also modelled. Energy dependent scatter kernels were created in Topas for two 16-cm diameter phantoms: A Catphan 515 contrast phantom and an anthropomorphic head phantom. The Catphan phantom contained inserts of 1-5 mm in diameter of six different tissue types. FastCAT simulations retain high fidelity to measurements and MC simulations: MTF curves were within 3.5% and 1.2% of measured values for the CWO and GOS detectors, respectively. HU values and CNR in a fastCAT Catphan 515 simulation were seen to be within 95 % confidence intervals of an equivalent MC simulation for all of the tissues with root mean squared errors less than 16 HU and 1.6 in HU values and CNR comparisons, respectively. A fastCAT simulation of the Catphan 515 module with an image size of 1024x1024x10 voxels took 61 seconds on a GPU while the equivalent Topas MC was estimated to take more than 0.3 CPU years. The fastCAT application can be found at https://github.com/jerichooconnell/fastCATs.git.
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