Jared Starman

Estimating the 0th and 1st moments in C-arm CT data for extrapolating truncated projections

C-Arm CT systems suffer from artifacts due to truncated projections caused by a finite detector size. One method used to mitigate the truncation artifacts is projection extrapolation without a priori knowledge. This work focuses on estimating the 0th and 1st moments of an image, which can be used to extrapolate a set of truncated projections. If some projections are not truncated, then accurate estimation of the moments can be achieved using only those projections. The more difficult case arises when all projections are truncated by some amount. For this case we make simplifying assumptions and fit the truncated projections with elliptical profiles. From this fit, we estimate the 0th and 1st moments of the original image. These estimated moments are then used to perform an extrapolation of the truncated projections, where each projection meets a constraint based on the 0th and 1st moments (moment extrapolation). This work focuses on how accurate moment estimates must be for moment extrapolation to be effective. The algorithm was tested on simulated and real data for the head, thorax, and abdomen, and those results were compared to symmetric mirroring by Ohnesorge et al., another extrapolation technique that requires no a priori knowledge. Overall, moment estimation and mass extrapolation alleviates a large amount of image artifact, and can improve on other extrapolation techniques. For the real CT head and abdominal data, the average reconstruction error for mass extrapolation was 48% less than the reconstruction error for symmetric mirroring.

Investigation into the optimal linear time-invariant lag correction for radar artifact removal

PURPOSE Detector lag, or residual signal, in amorphous silicon (a-Si) flat-panel (FP) detectors can cause significant shading artifacts in cone-beam computed tomography (CBCT) reconstructions. To date, most correction models have assumed a linear, time-invariant (LTI) model and lag is corrected by deconvolution with an impulse response function (IRF). However, there are many ways to determine the IRF. The purpose of this work is to better understand detector lag in the Varian 4030CB FP and to identify the IRF measurement technique that best removes the CBCT shading artifact. METHODS We investigated the linearity of lag in a Varian 4030CB a-Si FP operating in dynamic gain mode at 15 frames per second by examining the rising step-response function (RSRF) followed by the falling step-response function (FSRF) at ten incident exposures (0.5%-84% of a-Si FP saturation exposure). We implemented a multiexponential (N = 4) LTI model for lag correction and investigated the effects of various techniques for determining the IRF such as RSRF versus FSRF, exposure intensity, length of exposure, and spatial position. The resulting IRFs were applied to (1) the step-response projection data and (2) CBCT acquisitions of a large pelvic phantom and acrylic head phantom. For projection data, 1st and 50th frame lags were measured pre- and postcorrection. For the CBCT reconstructions, four pairs of ROIs were defined and the maximum and mean errors within each pair were calculated for the different exposures and step-response edge techniques. RESULTS A nonlinearity greater than 50% was observed in the FSRF data. A model calibrated with RSRF data resulted in overcorrection of FSRF data. Conversely, models calibrated with FSRF data applied to RSRF data resulted in undercorrection of the RSRF. Similar effects were seen when LTI models were applied to data collected at different incident exposures. Some spatial variation in lag was observed in the step-response data. For CBCT reconstructions, an average error range of 3-21 HU was observed when using IRFs from different techniques. For our phantoms and FP, the lowest average error occurred for the FSRF-based techniques at exposures of 1.6 or 3.4% a-Si FP saturation, depending on the phantom used. CONCLUSIONS The choice of step-response edge (RSRF versus FSRF) and exposure intensity for IRF calibration could leave large residual lag in the step-response data. For the CBCT reconstructions, IRFs derived from FSRF data at low exposure intensities (1.6 and 3.4%) best removed the CBCT shading artifact. Which IRF to use for lag correction could be selected based on the object size.

An Efficient Estimation Method for Reducing the Axial Intensity Drop in Circular Cone-Beam CT

Reconstruction algorithms for circular cone-beam (CB) scans have been extensively studied in the literature. Since insufficient data are measured, an exact reconstruction is impossible for such a geometry. If the reconstruction algorithm assumes zeros for the missing data, such as the standard FDK algorithm, a major type of resulting CB artifacts is the intensity drop along the axial direction. Many algorithms have been proposed to improve image quality when faced with this problem of data missing; however, development of an effective and computationally efficient algorithm remains a major challenge. In this work, we propose a novel method for estimating the unmeasured data and reducing the intensity drop artifacts. Each CB projection is analyzed in the Radon space via Grangeats first derivative. Assuming the CB projection is taken from a parallel beam geometry, we extract those data that reside in the unmeasured region of the Radon space. These data are then used as in a parallel beam geometry to calculate a correction term, which is added together with Hus correction term to the FDK result to form a final reconstruction. More approximations are then made on the calculation of the additional term, and the final formula is implemented very efficiently. The algorithm performance is evaluated using computer simulations on analytical phantoms. The reconstruction comparison with results using other existing algorithms shows that the proposed algorithm achieves a superior performance on the reduction of axial intensity drop artifacts with a high computation efficiency.

C-arm CT with XRIIs and digital flat panels: a review

C-arm CT first emerged as a useful high-contrast imaging modality in the late 1990s, using an XRII as the large area x-ray detector. To date, the C-arm approach to intra-procedural 3D imaging has primarily been used for high-contrast imaging tasks. The emerging goal for these systems is to extend the imaging range into the area of soft-tissue, and it is thought that digital flat-panel detectors may help. Flat panels replace the analog image intensifier, the camera optics, the pickup tube and the analog-to-digital converter with an all-digital detector. Flat panel detectors have a linear response, do not require distortion correction, do not suffer from veiling glare or blooming, and have higher dynamic range that current XRIIs. On the other hand, XRIIs have greater flexibility in FOV, and could support higher frame rates at high resolution, thereby reducing the effects of view aliasing. We have experience with a typical XRII-based C-arm imaging system and a new high-end C-arm equipped with a large flat-panel detector. Initial investigations show that when projection pixel size, acquisition geometry and focal spot size are matched, the flat-panel-based system produces reconstructions with improved MTF, primarily due to the additional interpolation step required for XRII warp correction. Investigations of artifact levels and comparison with in vivo CT images are presented.

A nonlinear lag correction algorithm for a‐Si flat‐panel x‐ray detectors

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 (N = 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.

A Patient Set-up Protocol Based on Partially Blocked Cone-beam CT

Three-dimensional x-ray cone-beam CT (CBCT) is being increasingly used in radiation therapy. Since the whole treatment course typically lasts several weeks, the repetitive x-ray imaging results in large radiation dose delivered on the patient. In the current radiation therapy treatment, CBCT is mainly used for patient set-up, and a rigid transformation of the CBCT data from the planning CT data is also assumed. For an accurate rigid registration, it is not necessary to acquire a full 3D image. In this paper, we propose a patient set-up protocol based on partially blocked CBCT. A sheet of lead strips is inserted between the x-ray source and the scanned patient. From the incomplete projection data, only several axial slices are reconstructed and used in the image registration for patient set-up. Since the radiation is partially blocked, the dose delivered onto the patient is significantly reduced, with an additional benefit of reduced scatter signals. The proposed approach is validated using experiments on two anthropomorphic phantoms. As x-ray beam blocking ratio increases, more dose reduction is achieved, while the patient set-up error also increases. To investigate this tradeoff, two lead sheets with different strip widths are implemented, which correspond to radiation dose reduction of ~6 and ~11, respectively. We compare the registration results using the partially blocked CBCT with those using the regular CBCT. Both lead sheets achieve high patient set-up accuracies. It is seen that, using the lead sheet with radiation dose reduction by a factor of ~11, the patient set-up error is still less than 1mm in translation and less than 0.2 degrees in rotation. The comparison of the reconstructed images also shows that the image quality of the illuminated slices in the partially blocked CBCT is much improved over that in the regular CBCT.

A forward bias method for lag correction of an a-Si flat panel detector.

PURPOSE Digital a-Si flat panel (FP) x-ray detectors can exhibit detector lag, or residual signal, of several percent that can cause ghosting in projection images or severe shading artifacts, known as the radar artifact, in cone-beam computed tomography (CBCT) reconstructions. A major contributor to detector lag is believed to be defect states, or traps, in the a-Si layer of the FP. Software methods to characterize and correct for the detector lag exist, but they may make assumptions such as system linearity and time invariance, which may not be true. The purpose of this work is to investigate a new hardware based method to reduce lag in an a-Si FP and to evaluate its effectiveness at removing shading artifacts in CBCT reconstructions. The feasibility of a novel, partially hardware based solution is also examined. METHODS The proposed hardware solution for lag reduction requires only a minor change to the FP. For pulsed irradiation, the proposed method inserts a new operation step between the readout and data collection stages. During this new stage the photodiode is operated in a forward bias mode, which fills the defect states with charge. A Varian 4030CB panel was modified to allow for operation in the forward bias mode. The contrast of residual lag ghosts was measured for lag frames 2 and 100 after irradiation ceased for standard and forward bias modes. Detector step response, lag, SNR, modulation transfer function (MTF), and detective quantum efficiency (DQE) measurements were made with standard and forward bias firmware. CBCT data of pelvic and head phantoms were also collected. RESULTS Overall, the 2nd and 100th detector lag frame residual signals were reduced 70%-88% using the new method. SNR, MTF, and DQE measurements show a small decrease in collected signal and a small increase in noise. The forward bias hardware successfully reduced the radar artifact in the CBCT reconstruction of the pelvic and head phantoms by 48%-81%. CONCLUSIONS Overall, the forward bias method has been found to greatly reduce detector lag ghosts in projection data and the radar artifact in CBCT reconstructions. The method is limited to improvements of the a-Si photodiode response only. A future hybrid mode may overcome any limitations of this method.

Parameter investigation and first results from a digital flat panel detector with forward bias capability

Digital flat panel a-Si x-ray detectors can exhibit image lag of several percent. The image lag can limit the temporal resolution of the detector, and introduce artifacts into CT reconstructions. It is believed that the majority of image lag is due to defect states, or traps, in the a-Si layer. Software methods to characterize and correct for the image lag exist, but they may make assumptions such as the system behaves in a linear time-invariant manner. The proposed method of reducing lag is a hardware solution that makes few additional hardware changes. For pulsed irradiation, the proposed method inserts a new stage in between the readout of the detector and the data collection stages. During this stage the photodiode is operated in a forward bias mode, which fills the defect states with charge. Parameters of importance are current per diode and current duration, which were investigated under light illumination by the following design parameters: 1.) forward bias voltage across the photodiode and TFT switch, 2.) number of rows simultaneously forward biased, and 3.) duration of the forward bias current. From measurements, it appears that good design criteria for the particular imager used are 8 or fewer active rows, 2.9V (or greater) forward bias voltage, and a row frequency of 100 kHz or less. Overall, the forward bias method has been found to reduce first frame lag by as much as 95%. The panel was also tested under x-ray irradiation. Image lag improved (94% reduction), but the temporal response of the scintillator became evident in the turn-on step response.

MTF measurement and a phantom study for scatter correction in CBCT using primary modulation

Recently, we proposed a scatter correction methods for X-ray imaging using primary modulation. A primary modulator with spatially variant attenuating materials is inserted between the X-ray source and the object to make the scatter and part of the primary distributions strongly separated in the Fourier domain. Linear filtering and demodulation techniques suffice to extract and correct the scatter for this modified system. The method has been verified by computer simulations and preliminary experimental results. In this work, we look into a hybrid method using both primary modulation and an anti-scatter grid. The reconstructed image resolution using the proposed approach is evaluated by MTF measurements, and the scatter correction performance is also investigated by experiments on a human chest phantom. The results using the proposed hybrid method are compared with those using an antiscatter grid only. Experiments with scatter inherently suppressed using a narrowly opened collimator and an anti-scatter grid (a slot-scan geometry) were also carried out. The comparison shows that the filtering in the proposed algorithm does not impair the image resolution, and the primary modulation method can effectively suppress the scatter artifacts. In the central region of interest, the reconstruction error relative to the image obtained using a slot-scan geometry is reduced from 18.10% to 0.48% for the human chest phantom, if the primary modulation method is used.

TH‐E‐330A‐04: Investigation Into the Cause of a New Artifact in Cone Beam CT Reconstructions On a Flat Panel Imager

Purpose: To investigate the source of and possible corrections for a new artifact seen in cone‐beam CT(CBCT)images acquired using an a‐Si flat panel imager(FPI) (Varian 4030CB). The new artifact is a bright circular region, tangent to the phantom edge, in images of elliptical and off‐center phantoms. Methods and Materials: Temporal response of the FPI was measured using a step‐wedge phantom, as a function of dose and irradiation history (10 cycles of 80 s exposure, with 9 off‐cycles varying in time between 2 and 30 minutes, total time 1hour 20 min). A linear time invariant (LTI) model was developed by fitting multi‐exponentials to the lag response from the step‐wedge phantom. Anthropomorphic phantoms — pelvis placed centrally, and head placed off‐center — were scanned and reconstructed with and without the developed correction. Results: Detector lag and continuous and significant monotonic gain increase (up to 10% for long irradiation periods) were observed during constant irradiation. Even after long periods of no exposure, with the detector being continuously read out, the gain did not return to the original, start‐of‐day value. Unlike Overdick et al., we did not see a saturation effect in the gain change. In CBCTreconstructions, differences up to 35 HU existed close to the edges of the artifact. After applying our correction model, differences were reduced to less than 10 HU. Our anthropomorphic phantoms did not generate streaks or comet tails, which other investigators have shown to be due to lag. Conclusion: We have determined that the source of the circular artifact observed is a non‐ideal temporal response. This artifact can be mostly eliminated by applying a correction based on a LTI model. Future work will focus on more accurate modeling to completely eliminate the artifact. Conflict of Interest: Funding was provided by Varian Medical Systems.