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Title: Reduction of ring artifacts in CBCT: Detection and correction of pixel gain variations in flat panel detectors

Abstract

Purpose: In using flat panel detectors (FPD) for cone beam computed tomography (CBCT), pixel gain variations may lead to structured nonuniformities in projections and ring artifacts in CBCT images. Such gain variations can be caused by change in detector entrance exposure levels or beam hardening, and they are not accounted by conventional flat field correction methods. In this work, the authors presented a method to identify isolated pixel clusters that exhibit gain variations and proposed a pixel gain correction (PGC) method to suppress both beam hardening and exposure level dependent gain variations. Methods: To modulate both beam spectrum and entrance exposure, flood field FPD projections were acquired using beam filters with varying thicknesses. “Ideal” pixel values were estimated by performing polynomial fits in both raw and flat field corrected projections. Residuals were calculated by taking the difference between measured and ideal pixel values to identify clustered image and FPD artifacts in flat field corrected and raw images, respectively. To correct clustered image artifacts, the ratio of ideal to measured pixel values in filtered images were utilized as pixel-specific gain correction factors, referred as PGC method, and they were tabulated as a function of pixel value in a look-up table. Results:more » 0.035% of detector pixels lead to clustered image artifacts in flat field corrected projections, where 80% of these pixels were traced back and linked to artifacts in the FPD. The performance of PGC method was tested in variety of imaging conditions and phantoms. The PGC method reduced clustered image artifacts and fixed pattern noise in projections, and ring artifacts in CBCT images. Conclusions: Clustered projection image artifacts that lead to ring artifacts in CBCT can be better identified with our artifact detection approach. When compared to the conventional flat field correction method, the proposed PGC method enables characterization of nonlinear pixel gain variations as a function of change in x-ray spectrum and intensity. Hence, it can better suppress image artifacts due to beam hardening as well as artifacts that arise from detector entrance exposure variation.« less

Authors:
 [1]; ; ;  [2]
  1. Department of Radiation Oncology, University of Colorado School of Medicine, Aurora, Colorado 80045 (United States)
  2. Department of Imaging Physics, University of Texas M.D. Anderson Cancer Center, Houston, Texas 77030 (United States)
Publication Date:
OSTI Identifier:
22409550
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 41; Journal Issue: 9; Other Information: (c) 2014 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
62 RADIOLOGY AND NUCLEAR MEDICINE; COMPUTERIZED TOMOGRAPHY; IMAGE PROCESSING; PHANTOMS; RADIATION QUALITY; X-RAY SPECTRA

Citation Formats

Altunbas, Cem, E-mail: caltunbas@gmail.com, Lai, Chao-Jen, Zhong, Yuncheng, and Shaw, Chris C. Reduction of ring artifacts in CBCT: Detection and correction of pixel gain variations in flat panel detectors. United States: N. p., 2014. Web. doi:10.1118/1.4893278.
Altunbas, Cem, E-mail: caltunbas@gmail.com, Lai, Chao-Jen, Zhong, Yuncheng, & Shaw, Chris C. Reduction of ring artifacts in CBCT: Detection and correction of pixel gain variations in flat panel detectors. United States. doi:10.1118/1.4893278.
Altunbas, Cem, E-mail: caltunbas@gmail.com, Lai, Chao-Jen, Zhong, Yuncheng, and Shaw, Chris C. 2014. "Reduction of ring artifacts in CBCT: Detection and correction of pixel gain variations in flat panel detectors". United States. doi:10.1118/1.4893278.
@article{osti_22409550,
title = {Reduction of ring artifacts in CBCT: Detection and correction of pixel gain variations in flat panel detectors},
author = {Altunbas, Cem, E-mail: caltunbas@gmail.com and Lai, Chao-Jen and Zhong, Yuncheng and Shaw, Chris C.},
abstractNote = {Purpose: In using flat panel detectors (FPD) for cone beam computed tomography (CBCT), pixel gain variations may lead to structured nonuniformities in projections and ring artifacts in CBCT images. Such gain variations can be caused by change in detector entrance exposure levels or beam hardening, and they are not accounted by conventional flat field correction methods. In this work, the authors presented a method to identify isolated pixel clusters that exhibit gain variations and proposed a pixel gain correction (PGC) method to suppress both beam hardening and exposure level dependent gain variations. Methods: To modulate both beam spectrum and entrance exposure, flood field FPD projections were acquired using beam filters with varying thicknesses. “Ideal” pixel values were estimated by performing polynomial fits in both raw and flat field corrected projections. Residuals were calculated by taking the difference between measured and ideal pixel values to identify clustered image and FPD artifacts in flat field corrected and raw images, respectively. To correct clustered image artifacts, the ratio of ideal to measured pixel values in filtered images were utilized as pixel-specific gain correction factors, referred as PGC method, and they were tabulated as a function of pixel value in a look-up table. Results: 0.035% of detector pixels lead to clustered image artifacts in flat field corrected projections, where 80% of these pixels were traced back and linked to artifacts in the FPD. The performance of PGC method was tested in variety of imaging conditions and phantoms. The PGC method reduced clustered image artifacts and fixed pattern noise in projections, and ring artifacts in CBCT images. Conclusions: Clustered projection image artifacts that lead to ring artifacts in CBCT can be better identified with our artifact detection approach. When compared to the conventional flat field correction method, the proposed PGC method enables characterization of nonlinear pixel gain variations as a function of change in x-ray spectrum and intensity. Hence, it can better suppress image artifacts due to beam hardening as well as artifacts that arise from detector entrance exposure variation.},
doi = {10.1118/1.4893278},
journal = {Medical Physics},
number = 9,
volume = 41,
place = {United States},
year = 2014,
month = 9
}
  • Our overall goal is to develop a new generation of electronic portal imaging devices (EPIDs) with a quantum efficiency (QE) more than an order of magnitude higher and a spatial resolution equivalent to that of EPIDs currently used for portal imaging. A novel design of such a high QE flat-panel based EPID was introduced recently and its feasibility was investigated theoretically [see Pang and Rowlands, Med. Phys. 31, 3004 (2004)]. In this work, we constructed a prototype single-pixel detector based on the novel design. Some fundamental imaging properties including the QE, spatial resolution, and sensitivity of the prototype detector weremore » measured with a 6 MV beam. It has been shown that the experimental results agree well with theoretical predictions and further development based on the novel design including the construction of a prototype area detector is warranted.« less
  • Active matrix flat-panel imager (AMFPI) technology is being employed for an increasing variety of imaging applications. An important element in the adoption of this technology has been significant ongoing improvements in optical signal collection achieved through innovations in indirect detection array pixel design. Such improvements have a particularly beneficial effect on performance in applications involving low exposures and/or high spatial frequencies, where detective quantum efficiency is strongly reduced due to the relatively high level of additive electronic noise compared to signal levels of AMFPI devices. In this article, an examination of various signal properties, as determined through measurements and calculationsmore » related to novel array designs, is reported in the context of the evolution of AMFPI pixel design. For these studies, dark, optical, and radiation signal measurements were performed on prototype imagers incorporating a variety of increasingly sophisticated array designs, with pixel pitches ranging from 75 to 127 {mu}m. For each design, detailed measurements of fundamental pixel-level properties conducted under radiographic and fluoroscopic operating conditions are reported and the results are compared. A series of 127 {mu}m pitch arrays employing discrete photodiodes culminated in a novel design providing an optical fill factor of {approx}80% (thereby assuring improved x-ray sensitivity), and demonstrating low dark current, very low charge trapping and charge release, and a large range of linear signal response. In two of the designs having 75 and 90 {mu}m pitches, a novel continuous photodiode structure was found to provide fill factors that approach the theoretical maximum of 100%. Both sets of novel designs achieved large fill factors by employing architectures in which some, or all of the photodiode structure was elevated above the plane of the pixel addressing transistor. Generally, enhancement of the fill factor in either discrete or continuous photodiode arrays was observed to result in no degradation in MTF due to charge sharing between pixels. While the continuous designs exhibited relatively high levels of charge trapping and release, as well as shorter ranges of linearity, it is possible that these behaviors can be addressed through further refinements to pixel design. Both the continuous and the most recent discrete photodiode designs accommodate more sophisticated pixel circuitry than is present on conventional AMFPIs - such as a pixel clamp circuit, which is demonstrated to limit signal saturation under conditions corresponding to high exposures. It is anticipated that photodiode structures such as the ones reported in this study will enable the development of even more complex pixel circuitry, such as pixel-level amplifiers, that will lead to further significant improvements in imager performance.« less
  • Purpose: The conditions under which vendor performance criteria for digital radiography systems are obtained do not adequately simulate the conditions of actual clinical imaging with respect to radiographic technique factors, scatter production, and scatter control. Therefore, the relationship between performance under ideal conditions and performance in clinical practice remains unclear. Using data from a large complement of systems in clinical use, the authors sought to develop a method to establish expected performance criteria for digital flat-panel radiography systems with respect to signal-to-noise ratio (SNR) versus detector exposure under clinical conditions for thoracic imaging. Methods: The authors made radiographic exposures ofmore » a patient-equivalent chest phantom at 125 kVp and 180 cm source-to-image distance. The mAs value was modified to produce exposures above and below the mAs delivered by automatic exposure control. Exposures measured free-in-air were corrected to the imaging plane by the inverse square law, by the attenuation factor of the phantom, and by the Bucky factor of the grid for the phantom, geometry, and kilovolt peak. SNR was evaluated as the ratio of the mean to the standard deviation (SD) of a region of interest automatically selected in the center of each unprocessed image. Data were acquired from 18 systems, 14 of which were tested both before and after gain and offset calibration. SNR as a function of detector exposure was interpolated using a double logarithmic function to stratify the data into groups of 0.2, 0.5, 1.0, 2.0, and 5.0 mR exposure (1.8, 4.5, 9.0, 18, and 45 {mu}Gy air KERMA) to the detector. Results: The mean SNR at each exposure interval after calibration exhibited linear dependence on the mean SNR before calibration (r{sup 2} = 0.9999). The dependence was greater than unity (m = 1.101 {+-} 0.006), and the difference from unity was statistically significant (p < 0.005). The SD of mean SNR after calibration also exhibited linear dependence on the SD of the mean SNR before calibration (r{sup 2} = 0.9997). This dependence was less than unity (m = 0.822 {+-} 0.008), and the difference from unity was also statistically significant (p < 0.005). Systems were separated into two groups: systems with a precalibration SNR higher than the median SNR (N = 7), and those with a precalibration SNR lower than the median SNR (N = 7). Posthoc analysis was performed to correct for expanded false positive results. After calibration, the authors noted differences in mean SNR within both high and low groups, but these differences were not statistically significant at the 0.05 level. SNR data from four additional systems and one system from those previously tested after replacement of its detector were compared to the 95% confidence intervals (CI) calculated from the postcalibration SNR data. The comparison indicated that four of these five systems were consistent with the CI derived from the previously tested 14 systems after calibration. Two systems from the paired group that remained outside the CI were studied further. One system was remedied with a grid replacement. The nonconformant behavior of the other system was corrected by replacing the image receptor. Conclusions: Exposure-dependent SNR measurements under conditions simulating thoracic imaging allowed us to develop criteria for digital flat-panel imaging systems from a single manufacturer. These measurements were useful in identifying systems with discrepant performance, including one with a defective grid, one with a defective detector, and one that had not been calibrated for gain and offset. The authors also found that the gain and offset calibration reduces variation in exposure-dependent SNR performance among the systems.« less
  • Purpose: Detector lag, or residual signal, in a-Si flat-panel (FP) detectors can cause significant shading artifacts in cone-beam computed tomography reconstructions. To date, most correction models have assumed a linear, time-invariant (LTI) model and correct lag by deconvolution with an impulse response function (IRF). However, the lag correction is sensitive to both the exposure intensity and the technique used for determining the IRF. Even when the LTI correction that produces the minimum error is found, residual artifact remains. A new non-LTI method was developed to take into account the IRF measurement technique and exposure dependencies. Methods: First, a multiexponential (Nmore » = 4) LTI model was implemented for lag correction. Next, a non-LTI lag correction, known as the nonlinear consistent stored charge (NLCSC) method, was developed based on the LTI multiexponential method. It differs from other nonlinear lag correction algorithms in that it maintains a consistent estimate of the amount of charge stored in the FP and it does not require intimate knowledge of the semiconductor parameters specific to the FP. For the NLCSC method, all coefficients of the IRF are functions of exposure intensity. Another nonlinear lag correction method that only used an intensity weighting of the IRF was also compared. The correction algorithms were applied to step-response projection data and CT acquisitions of a large pelvic phantom and an acrylic head phantom. The authors collected rising and falling edge step-response data on a Varian 4030CB a-Si FP detector operating in dynamic gain mode at 15 fps at nine incident exposures (2.0%-92% of the detector saturation exposure). For projection data, 1st and 50th frame lag were measured before and after correction. For the CT reconstructions, five pairs of ROIs were defined and the maximum and mean signal differences within a pair were calculated for the different exposures and step-response edge techniques. Results: The LTI corrections left residual 1st and 50th frame lag up to 1.4% and 0.48%, while the NLCSC lag correction reduced 1st and 50th frame residual lags to less than 0.29% and 0.0052%. For CT reconstructions, the NLCSC lag correction gave an average error of 11 HU for the pelvic phantom and 3 HU for the head phantom, compared to 14-19 HU and 2-11 HU for the LTI corrections and 15 HU and 9 HU for the intensity weighted non-LTI algorithm. The maximum ROI error was always smallest for the NLCSC correction. The NLCSC correction was also superior to the intensity weighting algorithm. Conclusions: The NLCSC lag algorithm corrected for the exposure dependence of lag, provided superior image improvement for the pelvic phantom reconstruction, and gave similar results to the best case LTI results for the head phantom. The blurred ring artifact that is left over in the LTI corrections was better removed by the NLCSC correction in all cases.« less
  • Purpose: Although x-ray projection mammography has been very effective in early detection of breast cancer, its utility is reduced in the detection of small lesions that are occult or in dense breasts. One drawback is that the inherent superposition of parenchymal structures makes visualization of small lesions difficult. Breast computed tomography using flat-panel detectors has been developed to address this limitation by producing three-dimensional data while at the same time providing more comfort to the patients by eliminating breast compression. Flat panels are charge integrating detectors and therefore lack energy resolution capability. Recent advances in solid state semiconductor x-ray detectormore » materials and associated electronics allow the investigation of x-ray imaging systems that use a photon counting and energy discriminating detector, which is the subject of this article. Methods: A small field-of-view computed tomography (CT) system that uses CdZnTe (CZT) photon counting detector was compared to one that uses a flat-panel detector for different imaging tasks in breast imaging. The benefits afforded by the CZT detector in the energy weighting modes were investigated. Two types of energy weighting methods were studied: Projection based and image based. Simulation and phantom studies were performed with a 2.5 cm polymethyl methacrylate (PMMA) cylinder filled with iodine and calcium contrast objects. Simulation was also performed on a 10 cm breast specimen. Results: The contrast-to-noise ratio improvements as compared to flat-panel detectors were 1.30 and 1.28 (projection based) and 1.35 and 1.25 (image based) for iodine over PMMA and hydroxylapatite over PMMA, respectively. Corresponding simulation values were 1.81 and 1.48 (projection based) and 1.85 and 1.48 (image based). Dose reductions using the CZT detector were 52.05% and 49.45% for iodine and hydroxyapatite imaging, respectively. Image-based weighting was also found to have the least beam hardening effect. Conclusions: The results showed that a CT system using an energy resolving detector reduces the dose to the patient while maintaining image quality for various breast imaging tasks.« less