Easy particle propagation (Epp) is a Monte Carlo simulation EGSnrc user code that we have developed for dose
calculation in a voxelized volume, and to generate images of an arbitrary geometry irradiated by a particle source.
The dose calculation aspect is a reimplementation of the function of DOSXYZnrc with new features added and
some restrictions removed. Epp is designed for x-ray application, but can be readily extended to trace other
kinds of particles.
Epp is based on the EGSnrc C++ class library (egspp) which makes modeling particle sources and simulation
geometries simpler than in DOSXYZnrc and other BEAM user codes based on EGSnrc code system. With Epp
geometries can be modeled analytically or voxelized geometries, such as those in DOSXYZnrc, can be used.
Compared to DOSXYZnrc (slightly modified from the official version for saving phase space information of
photons leaving the geometry), Epp is at least two times faster. Photon propagation to the image plane is
integrated into Epp (other particles possible with minor extension to the current code) with an ideal detector
defined. When only the resultant images are needed, there is no need to save the particle data. This results in
significant savings of data storage space, network load, and time for file I/O.
Epp was validated against DOSXYZnrc for imaging and dose calculation by comparing simulation results
with the same input. Epp can be used as a Monte Carlo simulation tool for faster imaging and radiation dose
applications.
We are investigating methods for computational scatter estimation for scatter correction in cone-beam computed
tomography. We have developed an analytical method for estimating single scatter. The paper discusses our analytical
method and its validation using Monte Carlo simulations. The paper extends previous results to include both Compton
and Rayleigh single scatter interactions. The paper also discusses the potential for hybrid scatter estimation, in which
empirical measurements of the total scatter signal in the collimator shadow may be used to augment computational single
scatter estimates and thus account for multiple scatter.
We have developed a method to estimate both the original objects and the blurring function from a sequence of noisy blurred images, simultaneously collected at different wavelengths (wavelength diversity). The assumption of common path-length errors across the diversity channels allows for a parallel deconvolution procedure that exploits this coupling. In contrast with previous work, no a priori assumptions about the object's intensity distribution are required. The method is described, and preliminary results for both synthetic computer-generated images and real images collected with a bench-scale imaging system are presented, demonstrating the promise of the algorithm.
The resolution of images captured through ground-based telescopes is generally limited by blurring effects due to atmospheric turbulence. We have developed a method to estimate both the original objects and the blurring function from a sequence of noisy blurred images, simultaneously collected at different wavelengths (wavelength diversity). The assumption of common path-length errors across the diversity channels allows for a parallel deconvolution procedure that exploits this coupling. In contrast with previous work, no a priori assumptions about the object’s intensity distribution are required. The method is described, and preliminary results with real images collected with a bench-scale imaging system are presented, demonstrating the promise of the algorithm.
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