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ObjectiveEvaluation of iodine quantification accuracy with varying iterative reconstruction level, patient habitus, and acquisition mode on a first-generation dual-source photon-counting computed tomography (PCCT) system.MethodsA multi-energy CT phantom (20 cm diameter/small) was imaged with and without an extension ring (30 by 40 cm/large). It was equipped with various iodine inserts (0.2, 0.5, 1.0, 2.0, 5.0, 10.0, 15.0 mg/ml) and scanned over a range of radiation dose levels (CTDIvol 0.5, 0.8, 1.2, 1.6, 2.0, 4.0, 6.0, 10.0, 15.0 mGy) using four different acquisition modes: single source 120 kVp (SS120), 140 kVp (SS140) and dual-source 120 kVp (DS120), 140 kVp (DS140). Iodine density maps were produced with different levels of iterative reconstruction (QIR 0, 2, 4). To assess the agreement between nominal and measured iodine concentrations, root mean square error (RMSE) and Bland-Altman plots were generated by grouping different radiation dose levels (ultra-low: < 1.5 mGy; low: 1.5 – 5 mGy; medium: 5 – 15 mGy) and iodine concentrations (low: < 5 mg/ml; high: 5 – 15 mg/ml).ResultsOverall, quantification of iodine concentrations was accurate and reliable even at ultra-low radiation dose levels. With low and high iodine concentrations, RMSE ranged from 0.25 to 0.37, 0.20 to 0.38, and 0.25 to 0.37 mg/ml for ultra-low, low, and medium radiation dose levels, respectively. Similarly, for the three acquisition modes (SS120, SS140, DS 120, DS140), RMSE was stable at 0.31, 0.28, 0.33 and 0.30 mg/ml, respectively. Considering all levels of radiation dose, acquisition mode, and iodine concentration, the accuracy of iodine quantification was higher for the phantom without extension ring (RMSE 0.21 mg/ml) and did not vary across different levels of iterative reconstruction.ConclusionsThe first-generation PCCT allows for accurate iodine quantification over a wide range of iodine concentrations and radiation dose levels. Even very small concentrations of iodine can be quantified accurately at different simulated patient sizes. Stable accuracy across iterative reconstruction levels may allow further radiation exposure reductions without affecting quantitative results.SummaryClinical photon-counting CT provides excellent iodine quantification performance for a wide range of parameters (patient habitus, acquisition parameters, and iterative reconstruction modes) due to its excellent ultra-low dose performance.Key ResultsFirst-generation PCCTs are capable of accurately quantifying iodine over a wide range of radiation dose levels and iodine concentrations.Further radiation exposure reductions may be possible given stable accuracy across iterative reconstruction levels.In the future, accurate and precise iodine quantification will allow for the development of spectral-based biomarkers.

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.

Conventional approaches in diffuse optical tomography (DOT) image reconstruction often address the ill-posed inverse problem via regularization with a constant penalty parameter, which uniformly smooths out the solution. In this study, we present a data-specific mask-guided scheme that incorporates a prior mask constraint into the image reconstruction framework. The prior mask was created from the DOT data itself by exploiting the multi-measurement vector formulation. We accordingly propose two methods to integrate the prior mask into the reconstruction process. First, as a soft prior by exploiting a spatially varying regularization. Second, as a hard prior by imposing a region-of-interest-limited reconstruction. Furthermore, the latter method iterates between discrete and continuous steps to update the mask and optical parameters, respectively. The proposed methods showed enhanced optical contrast accuracy, improved spatial resolution, and reduced noise level in DOT reconstructed images compared with the conventional approaches such as the modified Levenberg–Marquardt approach and the l 1 -regularization based sparse recovery approach.

Purpose As computed tomography (CT) imaging is the most commonly used modality for treatment planning in radiation therapy, metal artifacts in the planning CT images may complicate the target delineation and reduce the dose calculation accuracy. Although current CT scanners do provide certain correction steps, it is a common understanding that there is not a universal solution yet to the metal artifact reduction (MAR) in general. Particularly noting the importance of MAR for radiation treatment planning, we propose a novel MAR method in this work that recruits an additional tilted CT scan and synthesizes nearly metal‐artifact‐free CT images. Methods The proposed method is based on the facts that the most pronounced metal artifacts in CT images show up along the x‐ray beam direction traversing multiple metallic objects and that a tilted CT scan can provide complementary information free of such metal artifacts in the earlier scan. Although the tilted CT scan would contain its own metal artifacts in the images, the artifacts may manifest in a different fashion leaving a chance to concatenate the two CT images with the metal artifacts much suppressed. We developed an image processing technique that uses the structural similarity (SSIM) for suppressing the metal artifacts. On top of the additional scan, we proposed to use an existing MAR method for each scan if necessary to further suppress the metal artifacts. Results The proposed method was validated by a simulation study using the pelvic region of an XCAT numerical phantom and also by an experimental study using the head part of the Rando phantom. The proposed method was found to effectively reduce the metal artifacts. Quantitative analyses revealed that the proposed method reduced the mean absolute percentages of the error by up to 86% and 89% in the simulation and experimental studies, respectively. Conclusions It was confirmed that the proposed method, using complementary information acquired from an additional tilted CT scan, can provide nearly metal‐artifact‐free images for the treatment planning.

Cone-beam computed tomography (CBCT) is gaining widespread use in various medical and industrial applications but suffers from substantially larger amount of scatter than that in the conventional diagnostic CT resulting in relatively poor image quality. Various methods that can reduce and/or correct for the scatter in the CBCT have therefore been developed. Scatter correction method that uses a beam-blocker has been considered a direct measurement-based approach providing accurate scatter estimation from the data in the shadows of the beam-blocker. To the best of our knowledge, there has been no record reporting the significance of the scatter from the beam-blocker itself in such correction methods. In this paper, we identified the scatter from the beam-blocker that is detected in the object-free projection data investigated its influence on the image accuracy of CBCT reconstructed images, and developed a scatter correction scheme that takes care of this scatter as well as the scatter from the scanned object.

We propose a hybrid metal artifact reduction (MAR) approach for computed tomography (CT) that is computationally more efficient than a fully iterative reconstruction method, but at the same time achieves superior image quality to the interpolation-based in-painting techniques. Our proposed MAR method, an image-based artifact subtraction approach, utilizes an intermediate prior image reconstructed via PDART to recover the background information underlying the high density objects. For comparison, prior images generated by total-variation minimization (TVM) algorithm, as a realization of fully iterative approach, were also utilized as intermediate images. From the simulation and real experimental results, it has been shown that PDART drastically accelerates the reconstruction to an acceptable quality of prior images. Incorporating PDART-reconstructed prior images in the proposed MAR scheme achieved higher quality images than those by a conventional in-painting method. Furthermore, the results were comparable to the fully iterative MAR that uses high-quality TVM prior images.

Objective Various strategies have been developed in the past to reduce the excessive effects of metal artifacts in computed tomography images. From straightforward sinogram inpainting-based methods to computationally expensive iterative methods, all have been successful in improving the image quality up to a certain degree. We propose a novel image-based metal artifact subtraction method that achieves a superior image quality and at the same time provides a quantitatively more accurate image. Methods Our proposed method consists of prior image-based sinogram inpainting, metal sinogram extraction, and metal artifact image subtraction. Reconstructing the metal images from the extracted metal-contaminated portions in the sinogram yields a streaky image that eventually can be subtracted from the uncorrected image. The prior image is reconstructed from the sinogram that is free from the metal-contaminated portions by use of a total variation (TV) minimization algorithm, and the reconstructed prior image is fed into the forward projector so that the missing portions in the sinogram can be recovered. Image quality of the metal artifact-reduced images on selected areas was assessed by the structure similarity index for the simulated data and SD for the real dental data. Results Simulation phantom studies showed higher structure similarity index values for the proposed metal artifact reduction (MAR) images than the standard MAR images. Thus, more artifact suppression was observed in proposed MAR images. In real dental phantom data study, lower SD values were calculated from the proposed MAR images. The findings in real human arm study were also consistent with the results in all phantom studies. Thus, compared with standard MAR images, lesser artifact intensity was exhibited by the proposed MAR images. Conclusions From the quantitative calculations, our proposed method has shown to be effective and superior to the conventional approach in both simulation and real dental phantom cases.

Deep learning has been actively investigated for various applications such as image classification, computer vision, and regression tasks, and it has shown state-of-the-art performance. In diffuse optical tomography (DOT), the accurate estimation of the bulk optical properties of a medium is paramount because it directly affects the overall image quality. In this work, we exploit deep learning to propose a novel, to the best of our knowledge, convolutional neural network (CNN)-based approach to estimate the bulk optical properties of a highly scattering medium such as biological tissue in DOT. We validated the proposed method by using experimental, as well as, simulated data. For performance assessment, we compared the results of the proposed method with those of existing approaches. The results demonstrate that the proposed CNN-based approach for bulk optical property estimation outperforms existing methods in terms of estimation accuracy, with lower computation time.

Purpose: A beam-blocker composed of multiple strips is a useful gadget for scatter correction and/or for dose reduction in cone-beam CT (CBCT). However, the use of such a beam-blocker would yield cone-beam data that can be challenging for accurate image reconstruction from a single scan in the filtered-backprojection framework. The focus of the work was to develop an analytic image reconstruction method for CBCT that can be directly applied to partially blocked cone-beam data in conjunction with the scatter correction. Methods: The authors developed a rebinned backprojection-filteration (BPF) algorithm for reconstructing images from the partially blocked cone-beam data in a circular scan. The authors also proposed a beam-blocking geometry considering data redundancy such that an efficient scatter estimate can be acquired and sufficient data for BPF image reconstruction can be secured at the same time from a single scan without using any blocker motion. Additionally, scatter correction method and noise reduction scheme have been developed. The authors have performed both simulation and experimental studies to validate the rebinned BPF algorithm for image reconstruction from partially blocked cone-beam data. Quantitative evaluations of the reconstructed image quality were performed in the experimental studies. Results: The simulation study revealed that the developed reconstructionmore » algorithm successfully reconstructs the images from the partial cone-beam data. In the experimental study, the proposed method effectively corrected for the scatter in each projection and reconstructed scatter-corrected images from a single scan. Reduction of cupping artifacts and an enhancement of the image contrast have been demonstrated. The image contrast has increased by a factor of about 2, and the image accuracy in terms of root-mean-square-error with respect to the fan-beam CT image has increased by more than 30%. Conclusions: The authors have successfully demonstrated that the proposed scanning method and image reconstruction algorithm can effectively estimate the scatter in cone-beam projections and produce tomographic images of nearly scatter-free quality. The authors believe that the proposed method would provide a fast and efficient CBCT scanning option to various applications particularly including head-and-neck scan.« less

Various strategies have been developed to reduce metal artifacts in CT images, yet reduction of artifacts is successful to varying degrees. We proposed an image-based metal artifact reduction (MAR) approach incorporating an inpainting step, extraction of metal artifact-corrupted sinogram, and acquisition of a metal artifact-only image to reduce metal artifacts in an uncorrected image. In this work, a simulation study was conducted using a numerical pelvic phantom with bilateral metal inserts to demonstrate the effectiveness of the proposed method. For comparison, a conventional or standard sinogram inpainting method was also implemented. The proposed method produced visually comparable image quality to standard inpainting method. In addition, we particularly investigated the effects of the hard tissues, i.e. bones, that surround the metal on the MAR performance. We found that treating the surrounding bones together with the metals in the context of the proposed MAR scheme drastically reduces the metal artifacts that would otherwise overwhelm the image in conventional approaches.

This work proposed a motion detection method for cone-beam computed tomography (CBCT) that utilizes a calibration phantom of known geometry as the motion detector and an established geometric calibration protocol to provide the motion information. An initial numerical study regarding the consequences of motion and its correction was conducted with a Shepp-Logan and an XCAT phantom. Motion artifacts were induced by acquiring the projections in a simple saddle trajectory scan. Since the scanning trajectory is set, the magnitude of motion for each projection view is already known, the correction of motion can then be efficiently implemented. Motion correction was done prior to the backprojection process of the filtered backprojection (FBP) image reconstruction algorithm. Results showed that motion correction improved the image quality of the reconstructed images. For a known or unknown scanning trajectory, the geometric calibration method can define the geometric information of a scanning system. In the current work, projections of a calibration phantom of known geometry were acquired from a saddle trajectory scan, and geometric parameters for selected projection views were successfully computed from the projection matrix provided by the geometric calibration method. Further studies will involve an experimental investigation wherein a calibration phantom is attached to a randomly moving object and scanned in a circular trajectory. Utilizing the parameters extracted from the geometric calibration, an accurate description of the object motion can be used and adapted for motion correction.

In this work, we proposed a novel scatter correction method for a circular cone-beam computed tomography (CBCT) using a hardware-based approach that completes both data acquisition and scatter correction in a single rotation. We utilized (quasi-)redundancy in the circular cone-beam data, and applied the chord-based backprojection-filtration (BPF) algorithm to avoid the problem of filtering discontinuous data that would occur if conventional filtered-backprojection (FBP) algorithms were used. A single scan was performed on a cylindrical uniform phantom with beam-block strips between the source and the phantom, and the scatter was estimated for each projection from the data under the blocked regions. The beam-block strips (BBSs) were aligned parallel to the rotation axis, and the spacing between the strips was determined so that the data within the spaces constitute at least slightly more than the minimum data required for image reconstruction. The results showed that the image error due to scatter (about 30 % of the attenuation coefficient value) has been successfully corrected by the proposed algorithm.

Purpose: The purpose of our study is to reduce imaging radiation dose while maintaining image quality of region of interest (ROI) in X-ray fluoroscopy. A low-dose real-time ROI fluoroscopic imaging technique which includes graphics-processing-unit- (GPU-) accelerated image processing for brightness compensation and noise filtering was developed in this study. Methods: In our ROI fluoroscopic imaging, a copper filter is placed in front of the X-ray tube. The filter contains a round aperture to reduce radiation dose to outside of the aperture. To equalize the brightness difference between inner and outer ROI regions, brightness compensation was performed by use of a simple weighting method that applies selectively to the inner ROI, the outer ROI, and the boundary zone. A bilateral filtering was applied to the images to reduce relatively high noise in the outer ROI images. To speed up the calculation of our technique for real-time application, the GPU-acceleration was applied to the image processing algorithm. We performed a dosimetric measurement using an ion-chamber dosimeter to evaluate the amount of radiation dose reduction. The reduction of calculation time compared to a CPU-only computation was also measured, and the assessment of image quality in terms of image noise and spatial resolution wasmore » conducted. Results: More than 80% of dose was reduced by use of the ROI filter. The reduction rate depended on the thickness of the filter and the size of ROI aperture. The image noise outside the ROI was remarkably reduced by the bilateral filtering technique. The computation time for processing each frame image was reduced from 3.43 seconds with single CPU to 9.85 milliseconds with GPU-acceleration. Conclusion: The proposed technique for X-ray fluoroscopy can substantially reduce imaging radiation dose to the patient while maintaining image quality particularly in the ROI region in real-time.« less

Purpose: To reduce imagingradiationdose to the patient in cone‐beam CT(CBCT) for image‐guidedradiation therapy via intensity‐weighted region‐of‐interest (IWROI) imaging with a half‐fan geometry. Methods: An intensity‐weighting (IW) filter made of copper was mounted on the X‐ray tube unit of the on‐board imager (OBI) for CBCTdata acquisition. Since a half‐fan full‐scan mode is the choice of scanning for most treatment sites including the chest and the abdomen due to its enlarged field‐of‐view (FOV), the half‐fan scan mode has been used in this study. Accordingly, the IW filter was placed asymmetrically to cover outer part of the FOV. As a result, the region corresponding to the outer FOV was illuminated by the filtered beam during the scan. By sacrificing the image quality of the outer ROI‐region, one can reduce the overall imagingradiationdose to the patient dramatically. A humanoid abdomen phantom was used for the IWROI imaging experiment. Both the Feldkamp‐Davis‐Kress (FDK) and the chord‐ based backprojection‐filtration (BPF) algorithms were used for image reconstruction, and the results were compared. Correction of image artifacts caused by the edge of filter and the heterogeneity in beam‐quality was also made. Results: FDK algorithm produced images with artifacts when truncated data were used, whereas the BPF algorithm was capable of reconstructing exact ROI images without truncation artifacts from the truncated cone‐beam data. Dosimetric measurements are in progress to assess quantitative evaluation of imagingdose reduction. In addition, a feasibility study of image registration using the ROI images obtained by the proposed method is also going to be presented. Conclusions: The proposed half‐fan‐based IWROI imaging technique can be a valuable option for CBCT in IGRT applications, considering the substantial radiationdose imposed by the repeated use of conventional CBCT.