Harry R. Ingleby

Real data results with wavelength-diverse blind deconvolution.

Multiframe blind deconvolution is extended to incorporate simultaneous image acquisition at multiple wavelengths (wavelength diversity). The assumption of common path-length errors across the diversity channels allows for a parallel deconvolution procedure that exploits this coupling. No assumptions about variations in the objects intensity distribution at different wavelengths are required. The method is described and initial results for real images collected with a bench-scale imaging system are presented.

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

PURPOSE Easy particle propagation (Epp) is a user code for the EGSnrc code package based on the c+ + class library egspp. A main feature of egspp (and Epp) is the ability to use analytical objects to construct simulation geometries. The authors developed Epp to facilitate the simulation of x-ray imaging geometries, especially in the case of scatter studies. While direct use of egspp requires knowledge of c+ +, Epp requires no programming experience. METHODS Epps features include calculation of dose deposited in a voxelized phantom and photon propagation to a user-defined imaging plane. Projection images of primary, single Rayleigh scattered, single Compton scattered, and multiple scattered photons may be generated. Epp input files can be nested, allowing for the construction of complex simulation geometries from more basic components. To demonstrate the imaging features of Epp, the authors simulate 38 keV x rays from a point source propagating through a water cylinder 12 cm in diameter, using both analytical and voxelized representations of the cylinder. The simulation generates projection images of primary and scattered photons at a user-defined imaging plane. The authors also simulate dose scoring in the voxelized version of the phantom in both Epp and DOSXYZnrc and examine the accuracy of Epp using the Kawrakow-Fippel test. RESULTS The results of the imaging simulations with Epp using voxelized and analytical descriptions of the water cylinder agree within 1%. The results of the Kawrakow-Fippel test suggest good agreement between Epp and DOSXYZnrc. CONCLUSIONS Epp provides the user with useful features, including the ability to build complex geometries from simpler ones and the ability to generate images of scattered and primary photons. There is no inherent computational time saving arising from Epp, except for those arising from egspps ability to use analytical representations of simulation geometries. Epp agrees with DOSXYZnrc in dose calculation, since they are both based on the well-validated standard EGSnrc radiation transport physics model.

Experimental results of parallel multiframe blind deconvolution using wavelength diversity

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 objects 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.

Parallel multiframe blind deconvolution using wavelength diversity

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.

Analytical scatter estimation for cone-beam computed tomography

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.

Fast analytical scatter estimation using graphics processing units

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 NVIDIAs 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.

Epp - A C++ EGSnrc user code for Monte Carlo simulation of radiation transport

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.

Simultaneous estimation of the radioactivity distribution and electron density map from scattered coincidences in PET: A project overview

Quantitatively accurate PET images require correction of measured data for scattered coincidences. Additionally, an anatomical image is required to provide accurate attenuation correction and to facilitate the interpretation of the activity distribution. By taking advantage of accurately measured photon energies and the kinematics of Compton scattering, a 2D surface described by two circular arcs (TCA), which define the possible scattering loci and encompasses the annihilation position, can be identified. In 3D the annihilation is confined to the volume encompassed by the surface obtained by rotating the 2D arc around its axis. Using this premise, we have developed novel iterative reconstruction algorithms which use the scattered coincidences to 1) improve the activity distribution and 2) obtain an electron density map. The results have demonstrated the feasibility and benefits of incorporating scattered coincidences into the image reconstruction process. Incorporating scattered coincidences directly into the radiotracer reconstruction algorithm eliminates the need for scatter correction, and could improve both image quality and system sensitivity. The electron density map reconstructed from scattered coincidences can be directly applied to attenuation correction of the activity distribution, which removes energy scaling and registration problems.

Poster — Thur Eve — 21: Monte Carlo Simulation of X-Ray Scatter in Diagnostic Range with EGSnrc and GEANT4

In diagnostic x‐ray imaging, the attenuation of matter to x‐rays is substantially due to Compton and Rayleigh scattering in low Z materials. Consequently, the contrast of the x‐ray images is degraded by scatteredphotons. Because the total coherent scatter cross‐section is only about 10% of total Compton scatter cross‐section, Compton scatter plays a crucial role in x‐ray image quality. The x‐ray scatter effect can be corrected with experimentally measured or simulated data to improve image quality. It is necessary to acquire accurate x‐ray scatter information. Monte Carlo simulation is an important way of acquiring the x‐ray scatter information and the only practical way to analyze the Compton and Rayleigh scatter separately. However, due to the different ways of modeling the physics and various approximations in different Monte Carlo simulation packages, inconsistent simulation results have been observed. Using the Monte Carlo simulation packages of EGSnrc and GEANT4 we investigated the effects of the electron‐binding effects on the simulated x‐ray scattering in the diagnostic range. It is found that the Compton scatter and Rayleigh scatter are significantly different when simulated with different simulation packages and different physics models, e.g. with or without electron binding effect simulated. These differences are probably due to the ways the scattering process is modeled in the Monte Carlo simulation packages. Because the crucial role of simulated x‐ray scatter in scatter correcting in diagnostic imaging, improved modeling to the x‐ray scatter process in the Monte Carlo simulation package is desired.

Poster — Thur Eve — 34: Accelerated Analytical Scatter Estimation with Graphics Processing Units

Image degradation due to scatter can be a serious problem in x‐ray imaging, particularly in cone‐beam computed tomography because of the high scatter to primary ratio. Computational methods to estimate scatter are useful both for system modeling and optimization as well as algorithmic scatter correction. Computational scatter estimators are generally based on either Monte Carlo simulation or analytical calculations. Monte Carlo methods can incorporate very accurate models of interaction physics, but are typically very time consuming. Analytical methods, while usually less accurate than Monte Carlo due to simplifications required to render them computationally tractable, are more amenable to acceleration by parallelization. We previously developed an analytical method for estimating Compton and Rayleigh single scatter for a voxelized phantom in a cone beam geometry. Scatter estimates produced with our initial Matlab code showed good agreement with those obtained from Monte Carlo simulation of an identical imaging geometry in EGSnrc. Computation time with the analytical code was still significant, however, especially when using a high‐resolution phantom with small voxels. Our goal for this project was to accelerate our analytical scatter estimator, without loss of accuracy, by porting the code for use with Nvidia graphics processing units (GPUs) with the CUDA programming environment. Using four GPUs, we obtained speed‐up factors of approximately 700X relative to the original Matlab code running on a single CPU while maintaining good agreement with our reference Monte Carlo results. We plan to apply our GPU‐based analytical scatter estimator to a scatter correction algorithm for cone beam computed tomography.