Fast and accurate modeling of cone-beam CT (CBCT) x-ray projection data can improve CBCT image quality either
by linearizing projection data for each patient prior to image reconstruction (thereby mitigating detector blur/lag,
spectral hardening, and scatter artifacts) or indirectly by supporting rigorous comparative simulation studies of
competing image reconstruction and processing algorithms. In this study, we compare Monte Carlo-computed x-ray
projections with projections experimentally acquired from our Varian Trilogy CBCT imaging system for phantoms
of known design. Our recently developed Monte Carlo photon-transport code, PTRAN, was used to compute
primary and scatter projections for cylindrical phantom of known diameter (NA model 76-410) with and without
bow-tie filter and antiscatter grid for both full- and half-fan geometries. These simulations were based upon
measured 120 kVp spectra, beam profiles, and flat-panel detector (4030CB) point-spread function. Compound
Poisson- process noise was simulated based upon measured beam output. Computed projections were compared to
flat- and dark-field corrected 4030CB images where scatter profiles were estimated by subtracting narrow axial-from full axial width 4030CB profiles. In agreement with the literature, the difference between simulated and
measured projection data is of the order of 6-8%. The measurement of the scatter profiles is affected by the long tails
of the detector PSF. Higher accuracy can be achieved mainly by improving the beam modeling and correcting the
non linearities induced by the detector PSF.
KEYWORDS: Monte Carlo methods, X-rays, Photons, Sensors, Image filtering, Signal attenuation, X-ray imaging, Image quality, Signal to noise ratio, Calibration
The large contribution of scatter to cone-beam computed tomography (CBCT) x-ray projections significantly degrades
image quality, both through streaking and cupping artifacts and by loss of low contrast boundary detectability. The goal
of this investigation is to compare the efficacy of three widely used scatter mitigation methods: subtractive scatter
correction (SSC); anti-scatter grids (ASG); and beam modulating with bowtie filters; for improving signal-to-noise ratio
(SNR), contrast, contrast-to-noise ratio (CNR) and cupping artifacts. A simple analytic model was developed to predict
scatter-to-primary ratio (SPR) and CNR as a function of cylindrical phantom thickness. In addition, CBCT x-ray
projections of a CatPhan QA phantom were measured, using a Varian CBCT imaging system, and computed, using an
inhouse Monte Carlo photon-transport code to more realistically evaluate the impact of scatter mitigation techniques.
Images formed with uncorrected sinograms acquired without ASGs and bow-tie filter show pronounced cupping
artifacts and loss of contrast. Subtraction of measured scatter profiles restores image uniformity and CT number
accuracy, but does not improve CNR, since the improvement in contrast almost exactly offset by the increase in relative
x-ray noise. ASGs were found to modestly improve CNR (up to 20%, depending ASG primary transmission and
selectivity) only in body scans, while they can reduce CNR for head phantoms where SPR is low.
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