Epp: A <scp>C</scp>++ EGSnrc user code for x‐ray imaging and scattering simulations

Lippuner, Jonas; Elbakri, Idris A.; Cui, Chuan-Jue; Ingleby, Harry

doi:10.1118/1.3555296

Cited by 12 publications

(8 citation statements)

References 8 publications

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“…The simulation was implemented using EGSnrc MC software package [20] . This software package has been widely used to calculate the dose by simulating particle (photons, electron, and positron) interactions between photons and matter [21,23] . The easy particle propagation (Epp) [23] is a user code of EGSnrc to facilitate the simulation of X-ray imaging.…”

Section: Methodsmentioning

confidence: 99%

“…This software package has been widely used to calculate the dose by simulating particle (photons, electron, and positron) interactions between photons and matter [21,23] . The easy particle propagation (Epp) [23] is a user code of EGSnrc to facilitate the simulation of X-ray imaging. In Epp, the input parameters, including geometry, source type, beam geometry, object information, and other parameters, are defined in an input file.…”

Section: Methodsmentioning

confidence: 99%

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Investigation of dose for the triple-source computed tomography based on Monte Carlo Simulations

Zhao¹,

Chen²,

Yang³

et al. 2016

JBPR

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Triple-Source Computed Tomography (TSCT) improves the temporal resolution by three times the conventional Single-Source Computed Tomography (SSCT). The theories and implementations of TSCT have been well established in previous studies. However, whether additional X-ray tubes increase the dose remains unknown. To solve this problem, a TSCT system was simulated by Monte Carlo simulation. For comparison, an SSCT was also simulated under the same condition. The source models of SSCT and TSCT were validated against the experimental result obtained from a literature. In the simulation experiment, a digital human body phantom was scanned by the simulated computed tomography systems, and the dose was calculated. Result of the comparison revealed that the total absorbed doses of SSCT and TSCT were almost equal under the same data requirements and the dose distribution of TSCT was more even. Given no additional dose and the improved temporal resolution, TSCT is a promising tool for dynamic imaging.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Investigation of dose for the triple-source computed tomography based on Monte Carlo Simulations

Zhao¹,

Chen²,

Yang³

et al. 2016

JBPR

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“…The first study is to demonstrate the method with a dataset with low noise and no beam hardening. The primary and scatter data of the MASH phantom 16 were generated by EGSnrc, 17 which is a widely used Monte Carlo simulation package. The Monte Carlo simulation is time consuming.…”

Section: A Simulation Study With Low Noise and No Beam Hardeningmentioning

confidence: 99%

Optimization-based scatter estimation using primary modulation for computed tomography

Chen

Song

et al. 2016

Med. Phys.

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“…We thus validated our GPU-based analytical scatter estimates by comparing them to scatter estimates from EGSnrc MC simulations of an identical imaging geometry. We used Epp, a C++ user code for EGSnrc that provides built-in capabilities for simulating scatter images with a voxelized geometry [20]. The EGSnrc MC simulation parameters used are listed in Table 1.…”

Section: Validation Against Monte Carlo Simulationsmentioning

confidence: 99%

Fast analytical scatter estimation using graphics processing units

Ingleby

Lippuner

Rickey

et al. 2015

Journal of X-Ray Science and Technology: Clinical Applications

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PURPOSE: To develop a fast patient-specific analytical estimator of first-order Compton and Rayleigh scatter in cone-beam computed tomography, implemented using graphics processing units. METHODS:The authors developed an analytical estimator for first-order Compton and Rayleigh scatter in a cone-beam computed tomography geometry. The estimator was coded using NVIDIA's CUDA environment for execution on an NVIDIA graphics processing unit. Performance of the analytical estimator was validated by comparison with high-count Monte Carlo simulations for two different numerical phantoms. Monoenergetic analytical simulations were compared with monoenergetic and polyenergetic Monte Carlo simulations. Analytical and Monte Carlo scatter estimates were compared both qualitatively, from visual inspection of images and profiles, and quantitatively, using a scaled root-mean-square difference metric. Reconstruction of simulated cone-beam projection data of an anthropomorphic breast phantom illustrated the potential of this method as a component of a scatter correction algorithm. RESULTS: The monoenergetic analytical and Monte Carlo scatter estimates showed very good agreement. The monoenergetic analytical estimates showed good agreement for Compton single scatter and reasonable agreement for Rayleigh single scatter when compared with polyenergetic Monte Carlo estimates. For a voxelized phantom with dimensions 128 × 128 × 128 voxels and a detector with 256 × 256 pixels, the analytical estimator required 669 seconds for a single projection, using a single NVIDIA 9800 GX2 video card. Accounting for first order scatter in cone-beam image reconstruction improves the contrast to noise ratio of the reconstructed images. CONCLUSION: The analytical scatter estimator, implemented using graphics processing units, provides rapid and accurate estimates of single scatter and with further acceleration and a method to account for multiple scatter may be useful for practical scatter correction schemes.

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Epp: A C++ EGSnrc user code for x‐ray imaging and scattering simulations

Cited by 12 publications

References 8 publications

Investigation of dose for the triple-source computed tomography based on Monte Carlo Simulations

Investigation of dose for the triple-source computed tomography based on Monte Carlo Simulations

Optimization-based scatter estimation using primary modulation for computed tomography

Fast analytical scatter estimation using graphics processing units

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