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- 实验方案
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A weighted rebinned backprojection-Filtration algorithm from partially beam-blocked data for a single-scan cone-beam CT with hybrid type scatter correction
摘要： Purpose: Scatter contamination constitutes a dominant source of degradation of image quality in cone-beam computed tomography (CBCT). We have recently developed an analytic image reconstruction method with a scatter correction capability from the partially blocked cone-beam data out of a single scan. Despite its easy implementation and its computational efficiency, the developed method may result in additional image artifacts for a large cone angle geometry due to data inconsistency. To improve the image quality at a large cone angle, we propose a weighted rebinned backprojection-filtration (wrBPF) algorithm in conjunction with a hybrid type scatter correction approach. Methods: The proposed method uses a beam blocker array that provides partial data for scatter correction and image reconstruction and that only blocks the beam within a limited cone angle. This design allows a chance to keep the image quality at larger cone angles by use of data redundancy since the projection data corresponding to larger cone angles are not blocked. However, the scatter correction would not be straightforward. In order to correct for the scatter in the projections at larger cone angles, we propose a novel scatter correction method combining a measurement-based and a convolution-based method. We first estimated the scatter signal using a measurement-based method in the partially beam-blocked regions, and then optimized the fitting parameters of a convolution-kernel that can be used for scatter correction in the projections at larger cone angles. For image reconstruction, we developed a wrBPF with butterfly filtering. We have conducted an experimental study to validate the proposed algorithm for image reconstruction and scatter correction. Results: The experimental results revealed that the developed reconstruction method makes full use of the benefits of partial beam-blocking for scatter correction and image reconstruction and at the same time enhances image quality at larger cone angles by use of an optimized convolution-based scatter correction. Conclusions: The proposed method that enjoys the advantages of both measurement-based and convolution-based methods for scatter correction has successfully demonstrated its capability of reconstructing accurate images out of a single scan in circular CBCT.
关键词： X-ray beam-blocker,Cone-beam CT,Image reconstruction,Scatter correction,BPF
更新于2025-09-23 15:23:52
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An interprojection sensor fusion approach to estimate blocked projection signal in synchronized moving grid-based CBCT system
摘要： Purpose: A preobject grid can reduce and correct scatter in cone beam computed tomography (CBCT). However, half of the signal in each projection is blocked by the grid. A synchronized moving grid (SMOG) has been proposed to acquire two complimentary projections at each gantry position and merge them into one complete projection. That approach, however, suffers from increased scanning time and the technical difficulty of accurately merging the two projections per gantry angle. Herein, the authors present a new SMOG approach which acquires a single projection per gantry angle, with complimentary grid patterns for any two adjacent projections, and use an interprojection sensor fusion (IPSF) technique to estimate the blocked signal in each projection. The method may have the additional benefit of reduced imaging dose due to the grid blocking half of the incident radiation. Methods: The IPSF considers multiple paired observations from two adjacent gantry angles as approximations of the blocked signal and uses a weighted least square regression of these observations to finally determine the blocked signal. The method was first tested with a simulated SMOG on a head phantom. The signal to noise ratio (SNR), which represents the difference of the recovered CBCT image to the original image without the SMOG, was used to evaluate the ability of the IPSF in recovering the missing signal. The IPSF approach was then tested using a Catphan phantom on a prototype SMOG assembly installed in a bench top CBCT system. Results: In the simulated SMOG experiment, the SNRs were increased from 15.1 and 12.7 dB to 35.6 and 28.9 dB comparing with a conventional interpolation method (inpainting method) for a projection and the reconstructed 3D image, respectively, suggesting that IPSF successfully recovered most of blocked signal. In the prototype SMOG experiment, the authors have successfully reconstructed a CBCT image using the IPSF-SMOG approach. The detailed geometric features in the Catphan phantom were mostly recovered according to visual evaluation. The scatter related artifacts, such as cupping artifacts, were almost completely removed. Conclusions: The IPSF-SMOG is promising in reducing scatter artifacts and improving image quality while reducing radiation dose.
关键词： moving grids,scatter correction,interpolation,sensor fusion,geometric model,SMOG,dose reduction,CBCT
更新于2025-09-23 15:22:29
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An improved weighted multiplicative scatter correction algorithm with the use of variable selection: Application to near-infrared spectra
摘要： Multiplicative light scattering has posed great challenge in near-infrared (NIR) quantitative analysis. When estimating the scattering parameters, uninformative variables for scattering effects may bias the estimation. Weighted least squares (WLS) can be used to avoid the influence of the uninformative variables. In this work, we proposed an improved weighted multiplicative scatter correction algorithm with the use of variable selection (WMSCVS). Baseline is removed first and then variable selection is used to obtain the optimal weights of WLS in estimating multiplicative parameters. The variable selection algorithm, which is designed based on model population analysis (MPA), implements an iterative optimization process. In each iteration, weighted bootstrap sampling (WBS) is used to generate variable subsets and exponentially decreasing function (EDF) is used to control the number of sampled variables. The interpretability and stability of the variable selection results as well as the predictive performance of the corrected spectra were investigated by using two NIR datasets. The experimental results showed that the proposed WMSCVS could give better predictive performance than the state-of-art correction methods.
关键词： Model population analysis,Weighted least squares,Multiplicative scatter correction,Variable selection
更新于2025-09-19 17:15:36
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Scatter Correction in Cone Beam CT for Metal Additive Manufacturing Components
摘要： This paper provides an x-ray scatter correction method for cone beam computed tomography (CT) to reduce cupping artifacts and image inhomogeneity of metal additive manufacturing (AM) components. Firstly, projections in 360° were obtained by a cone beam CT system. Secondly, the corresponding virtual CT system was built on Geant4 to obtain scatter photons. Different from previous studies, the geometry of the metal AM component was set by importing a CAD model of the component into Geant4, which can not only assure the accuracy of geometry but also simplify the de?nition of the geometry. Finally, the corresponding scatter photons were subtracted from the experimental projections in 360° to obtain corrected projections. Corrected reconstruction images were acquired via an FDK algorithm. In the corrected images, the average sum of squares of deviation of regions of interest was about 79.5% of that in the uncorrected images. Corrected images showed that cupping-shaped artifacts and image inhomogeneity were effectively reduced.
关键词： scatter correction,CADMesh,Geant4,metal additive manufacturing,cone beam CT
更新于2025-09-10 09:29:36
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[IEEE 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) - Atlanta, GA (2017.10.21-2017.10.28)] 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) - Deep residual learning in CT physics: scatter correction for spectral CT
摘要： Recently, spectral CT has been drawing a lot of attention in a variety of clinical applications primarily due to its capability of providing quantitative information about material properties. The quantitative integrity of the reconstructed data depends on the accuracy of the data corrections applied to the measurements. Scatter correction is a particularly sensitive correction in spectral CT as it depends on system effects as well as the object being imaged and any residual scatter is amplified during the non-linear material decomposition. An accurate way of removing scatter is subtracting the scatter estimated by Monte Carlo simulation. However, to get sufficiently good scatter estimates, extremely large numbers of photons are required, which may lead to unexpectedly high computational costs. Other approaches model scatter as a convolution operation using kernels derived using empirical methods. These techniques have been found to be insufficient in spectral CT due to their inability to sufficiently capture object dependence. In this work, we develop a deep residual learning framework to address both issues of computation simplicity and object dependency. A deep convolution neural network is trained to determine the scatter distribution from the projection content in training sets. In test cases of a digital anthropomorphic phantom and real water phantom, we demonstrate that with much lower computing costs, the proposed network provides sufficiently accurate scatter estimation.
关键词： convolutional neural network,deep residual learning,Monte Carlo simulation,scatter correction,spectral CT
更新于2025-09-09 09:28:46