A filtered backprojection algorithm for triple-source helical cone-beam CT

TT U-Net: Temporal Transformer U-Net for Motion Artifact Reduction Using PAD (Pseudo All-Phase Clinical-Dataset) in Cardiac CT

Involuntary motion of the heart remains a challenge for cardiac computed tomography (CT) imaging. Although the electrocardiogram (ECG) gating strategy is widely adopted to perform CT scans at the quasi-quiescent cardiac phase, motion-induced artifacts are still unavoidable for patients with high heart rates or irregular rhythms. Dynamic cardiac CT, which provides functional information of the heart, suffers even more severe motion artifacts. In this paper, we develop a deep learning based framework for motion artifact reduction in dynamic cardiac CT. First, we build a PAD (Pseudo All-phase clinical-Dataset) based on a whole-heart motion model and single-phase cardiac CT images. This dataset provides dynamic CT images with realistic-looking motion artifacts that help to develop data-driven approaches. Second, we formulate the problem of motion artifact reduction as a video deblurring task according to its dynamic nature. A novel TT U-Net (Temporal Transformer U-Net) is proposed to excavate the spatiotemporal features for better motion artifact reduction. The self-attention mechanism along the temporal dimension effectively encodes motion information and thus aids image recovery. Experiments show that the TT U-Net trained on the proposed PAD performs well on clinical CT scans, which substantiates the effectiveness and fine generalization ability of our method. The source code, trained models, and dynamic demo will be available at https://github.com/ivy9092111111/TT-U-Net.

Geometry calibration and image reconstruction for carbon-nanotube-based multisource and multidetector CT

Conventional intraoperative computed tomography (CT) has a long scan time, degrading the image quality. Its large size limits the position of a surgeon during surgery. Therefore, this study proposes a CT system comprising of eight carbon-nanotube (CNT)-based x-ray sources and 16 detector modules to solve these limitations. Gantry only requires 45° of rotation to acquire the whole projection, reducing the scan time to 1/8 compared to the full rotation. Moreover, the volume and scan time of the system can be significantly reduced using CNT sources with a small volume and short pulse width and placing a heavy and large high-voltage generator outside the gantry. We divided the proposed system into eight subsystems and sequentially devised a geometry calibration method for each subsystem. Accordingly, a calibration phantom consisting of four polytetrafluoroethylene beads, each with 15 mm diameter, was designed. The geometry calibration parameters were estimated by minimizing the difference between the measured bead projection and the forward projection of the formulated subsystem. By reflecting the estimated geometry calibration parameters, the projection data were obtained via rebinning to be used in the filtered-backprojection reconstruction. The proposed calibration and reconstruction methods were validated by computer simulations and real experiments. Additionally, the accuracy of the geometry calibration method was examined by computer simulation. Furthermore, we validated the improved quality of the reconstructed image through the mean-squared error (MSE), structure similarity (SSIM), and visual inspections for both the simulated and experimental data. The results show that the calibrated images, reconstructed by reflecting the calibration results, have smaller MSE and higher SSIM values than the uncalibrated images. The calibrated images were observed to have fewer artifacts than the uncalibrated images in visual inspection, demonstrating that the proposed calibration and reconstruction methods effectively reduce artifacts caused by geometry misalignments.

FBP-type CT reconstruction algorithms for triple-source circular trajectory with different scanning radii

Multi-source computed tomography (CT) imaging has unique technical advantages not only for dynamic objects, but also for large-size objects by designing its imaging scan mode. Using the triple-source fan-beam imaging scan mode under three circular trajectories with two different radii, we in this study developed and analyzed theoretically several exact reconstruction algorithms in terms of full-scan and short-scan for three sets of truncated projection data. This triple-source scan configuration in different radii cases is easier to be simulated by a single-source scan configuration in an industrial CT system. The proposed algorithms are based on the idea of filtering-back-projection (FBP) algorithm, and can reconstruct the large-size objects under the same CT devices. The developed algorithms avoid data rebinning and can provide exact and fast image reconstruction. The results of the numerical simulation based data analysis verified that new algorithms were accurate and effective.

Physics Model-Based Scatter Correction in Multi-Source Interior Computed Tomography

Multi-source interior computed tomography (CT) has a great potential to provide ultra-fast and organ-oriented imaging at low radiation dose. However, X-ray cross scattering from multiple simultaneously activated X-ray imaging chains compromises imaging quality. Previously, we published two hardware-based scatter correction methods for multi-source interior CT. Here, we propose a software-based scatter correction method, with the benefit of no need for hardware modifications. The new method is based on a physics model and an iterative framework. The physics model was derived analytically, and was used to calculate X-ray scattering signals in both forward direction and cross directions in multi-source interior CT. The physics model was integrated to an iterative scatter correction framework to reduce scatter artifacts. The method was applied to phantom data from both Monte Carlo simulations and physical experimentation that were designed to emulate the image acquisition in a multi-source interior CT architecture recently proposed by our team. The proposed scatter correction method reduced scatter artifacts significantly, even with only one iteration. Within a few iterations, the reconstructed images fast converged toward the "scatter-free" reference images. After applying the scatter correction method, the maximum CT number error at the region-of-interests (ROIs) was reduced to 46 HU in numerical phantom dataset and 48 HU in physical phantom dataset respectively, and the contrast-noise-ratio at those ROIs increased by up to 44.3% and up to 19.7%, respectively. The proposed physics model-based iterative scatter correction method could be useful for scatter correction in dual-source or multi-source CT.

Theoretically exact backprojection filtration algorithm for multi-segment linear trajectory

A theoretically exact backprojection filtration algorithm is proved and implemented for image reconstruction from a multi-segment linear trajectory assuming fan-beam geometry. The reconstruction formula is based on a concept of linear PI-line (L-PI) proposed in our previous work. The proof is completed in two consecutive steps. In the first step, it is proved that theoretically exact image reconstruction can be obtained on an arbitrary L-PI line from an infinite straight-line trajectory. In the second step, it is shown that accurate image reconstruction can be achieved from a multi-segment line trajectory by introducing a weight function to deal with the data redundancy. Numerical implementation and simulation results validate the correctness of our theoretical results.

X-ray scatter correction for multi-source interior computed tomography

PURPOSE

The schemes of multi-source interior computed tomography (CT) have shown promise for ultra-fast, organ-oriented, and low-dose dynamic imaging. Besides forward scattering, x-ray cross scattering from multiple x-ray sources activated simultaneously can further degrade image quality. Here, we investigate the overall x-ray scattering artifact in a recently proposed multi-source interior CT architecture, and present two methods for scatter correction.

METHODS

Compared to single-source global CT, scattering in multi-source interior CT architecture is affected by two new factors: cross scattering from simultaneously activated multiple x-ray sources and region-of-interest (ROI) oriented interior CT mode. The scatter artifact in the multi-source interior CT architecture was evaluated through both numerical simulation and physical experimentation, and compared to that from conventional single-source global CT. Monte Carlo simulation was conducted with a modified numerical CATphan^® 600 phantom. Physical experiments were performed in an in-house developed CT imaging platform with a custom-built phantom. The simulation and experiments were carried out on the single-source CT architecture and the multi-source CT architecture, respectively in the global CT mode and the interior CT mode for comparison. To correct the scattering artifact, two new methods were presented. The first is a beam-stopper-array (BSA)-based method, which enables an online correction of forward scattering and cross scattering simultaneously. The second is a source-trigger-sequence (STS)-based method dedicated to cross-scatter correction. It enables on-the-fly measurements of the cross scattering signals at a few pre-selected views. The CT image quality was quantitatively evaluated in terms of contrast-to-noise ratio (CNR) and CT number deviation before and after the scatter correction.

RESULTS

X-ray cross scattering degraded image quality in both the simulation and experiments. Before the scatter correction, the multi-source interior CT mode yielded a reduction of CNR at the ROIs by up to 68.5% and 50.7% in the simulation and experiments, respectively. The stationary BSA-based method significantly improved CNR and CT number accuracy in the images from multi-source interior CT mode, by reducing the negative effects from both forward scattering and cross scattering. The STS-based method enabled multi-source interior CT mode to provide comparable image quality to that with the single-source interior CT mode, by correcting the artifact from cross scattering. The remaining forward scattering artifact can be corrected with the fast adaptive scatter kernel superposition (FASKS) technique. With the proposed scatter correction methods, the CT number error at the ROIs was reduced to less than 37 HU in both simulation and experiments, respectively.

CONCLUSIONS

Cross scattering, in addition to forward scattering, can cause significant image quality degradation in the multi-source interior CT architecture. However, image quality can be significantly improved with the proposed scatter correction methods.

CT of the Abdomen with Reduced Tube Voltage in Adults: A Practical Approach

Recent innovations in computed tomographic (CT) hardware and software have allowed implementation of low tube voltage imaging into everyday CT scanning protocols in adults. CT at a low tube voltage setting has many benefits, including (a) radiation dose reduction, which is crucial in young patients and those with chronic medical conditions undergoing serial CT examinations for disease management; and (b) higher contrast enhancement. For the latter, increased attenuation of iodinated contrast material improves the evaluation of hypervascular lesions, vascular structures, intestinal mucosa in patients with bowel disease, and CT urographic images. Additionally, the higher contrast enhancement may provide diagnostic images in patients with renal dysfunction receiving a reduced contrast material load and in patients with suboptimal peripheral intravenous access who require a lower contrast material injection rate. One limitation is that noisier images affect image quality at a low tube voltage setting. The development of denoising algorithms such as iterative reconstruction has made it possible to perform CT at a low tube voltage setting without compromising diagnostic confidence. Other potential pitfalls of low tube voltage CT include (a) photon starvation artifact in larger patients, (b) accentuation of streak artifacts, and (c) alteration of the CT attenuation value, which may affect evaluation of lesions on the basis of conventional enhancement thresholds. CT of the abdomen with a low tube voltage setting is an excellent radiation reduction technique when properly applied to imaging of select patients in the appropriate clinical setting.

Analytic reconstruction algorithms for triple-source CT with horizontal data truncation

PURPOSE

This paper explores a triple-source imaging method with horizontal data truncation to enlarge the field of view (FOV) for big objects.

METHODS

The study is conducted by using theoretical analysis, mathematical deduction, and numerical simulations. The proposed algorithms are implemented in c + + and matlab. While the basic platform is constructed in matlab, the computationally intensive segments are coded in c + +, which are linked via a mex interface.

RESULTS

A triple-source circular scanning configuration with horizontal data truncation is developed, where three pairs of x-ray sources and detectors are unevenly distributed on the same circle to cover the whole imaging object. For this triple-source configuration, a fan-beam filtered backprojection-type algorithm is derived for truncated full-scan projections without data rebinning. The algorithm is also extended for horizontally truncated half-scan projections and cone-beam projections in a Feldkamp-type framework. Using their method, the FOV is enlarged twofold to threefold to scan bigger objects with high speed and quality. The numerical simulation results confirm the correctness and effectiveness of the developed algorithms.

CONCLUSIONS

The triple-source scanning configuration with horizontal data truncation cannot only keep most of the advantages of a traditional multisource system but also cover a larger FOV for big imaging objects. In addition, because the filtering is shift-invariant, the proposed algorithms are very fast and easily parallelized on graphic processing units.

A quantitative comparison of noise reduction across five commercial (hybrid and model-based) iterative reconstruction techniques: an anthropomorphic phantom study

OBJECTIVE. The objective of our study was to compare the performance of three hybrid iterative reconstruction techniques (IRTs) (ASiR, iDose4, SAFIRE) and their respective strengths for image noise reduction on low-dose CT examinations using filtered back projection (FBP) as the standard reference. Also, we compared the performance of these three hybrid IRTs with two model-based IRTs (Veo and IMR) for image noise reduction on low-dose examinations. MATERIALS AND METHODS. An anthropomorphic abdomen phantom was scanned at 100 and 120 kVp and different tube current-exposure time products (25-100 mAs) on three CT systems (for ASiR and Veo, Discovery CT750 HD; for iDose4 and IMR, Brilliance iCT; and for SAFIRE, Somatom Definition Flash). Images were reconstructed using FBP and using IRTs at various strengths. Nine noise measurements (mean ROI size, 423 mm(2)) on extracolonic fat for the different strengths of IRTs were recorded and compared with FBP using ANOVA. Radiation dose, which was measured as the volume CT dose index and dose-length product, was also compared. RESULTS. There were no significant differences in radiation dose and image noise among the scanners when FBP was used (p > 0.05). Gradual image noise reduction was observed with each increasing increment of hybrid IRT strength, with a maximum noise suppression of approximately 50% (48.2-53.9%). Similar noise reduction was achieved on the scanners by applying specific hybrid IRT strengths. Maximum noise reduction was higher on model-based IRTs (68.3-81.1%) than hybrid IRTs (48.2-53.9%) (p < 0.05). CONCLUSION. When constant scanning parameters are used, radiation dose and image noise on FBP are similar for CT scanners made by different manufacturers. Significant image noise reduction is achieved on low-dose CT examinations rendered with IRTs. The image noise on various scanners can be matched by applying specific hybrid IRT strengths. Model-based IRTs attain substantially higher noise reduction than hybrid IRTs irrespective of the radiation dose.

Comparative assessment of three image reconstruction techniques for image quality and radiation dose in patients undergoing abdominopelvic multidetector CT examinations

OBJECTIVE

To compare image quality and radiation dose of abdominal CT examinations reconstructed with three image reconstruction techniques.

METHODS

In this Institutional Review Board-approved study, contrast-enhanced (CE) abdominopelvic CT scans from 23 patients were reconstructed using filtered back projection (FBP), adaptive statistical iterative reconstruction (ASiR) and iterative reconstruction in image space (IRIS) and were reviewed by two blinded readers. Subjective (acceptability, sharpness, noise and artefacts) and objective (noise) measures of image quality were recorded for each image data set. Radiation doses in CT dose index (CTDI) dose-length product were also calculated for each examination type and compared. Imaging parameters were compared using the Wilcoxon signed rank test and a paired t-test.

RESULTS

All 69 CECT examinations were of diagnostic quality and similar for overall acceptability (mean grade for ASiR, 3.9±0.3; p=0.2 for Readers 1 and 2; IRIS, 3.9±0.4, p=0.2; FBP, 3.8±0.9). Objective noise was considerably lower with both iterative techniques (p<0.0001 and 0.0016 for ASiR and IRIS). Recorded mean radiation dose, i.e. CTDI(vol), was 24% and 10% less with ASiR (11.4±3.4 mGy; p<0.001) and IRIS (13.5±3.7 mGy; p=0.06), respectively, than with FBP: 15.0±3.5 mGy.

CONCLUSION

At the system parameters used in this study, abdominal CT scans reconstructed with ASiR and IRIS provide diagnostic images with reduced image noise and 10-24% lower radiation dose than FBP.

ADVANCES IN KNOWLEDGE

CT images reconstructed with FBP are frequently noisy on lowering the radiation dose. Newer iterative reconstruction techniques have different approaches to produce images with less noise; ASiR and IRIS provide diagnostic abdominal CT images with reduced image noise and radiation dose compared with FBP. This has been documented in this study.

Impact of iterative reconstruction on image quality and radiation dose in multidetector CT of large body size adults

OBJECTIVE

To compare image quality and radiation dose using Adaptive Statistical Iterative Reconstruction (ASiR) and Filtered Back Projection (FBP) in patients weighing ≥ 91 kg.

METHODS

In this Institution Review Board-approved retrospective study, single-phase contrast-enhanced abdominopelvic CT examinations of 100 adults weighing ≥ 91 kg (mean body weight: 107.6 ± 17.4 kg range: 91-181.9 kg) with (1) ASiR and (2) FBP were reviewed by two readers in a blinded fashion for subjective measures of image quality (using a subjective standardized numerical scale and objective noise) and for radiation exposure. Imaging parameters and radiation dose results of the two techniques were compared within weight and BMI sub-categories.

RESULTS

All examinations were found to be of adequate quality. Both subjective (mean = 1.4 ± 0.5 vs. 1.6 ± 0.6, P < 0.05) and objective noise (13.0 ± 3.2 vs.19.5 ± 5.7, P < 0.0001) were lower with ASiR. Average radiation dose reduction of 31.5 % was achieved using ASiR (mean CTDIvol. ASiR: 13.5 ± 7.3 mGy; FBP: 19.7 ± 9.0 mGy, P < 0.0001). Other measures of image quality were comparable between the two techniques. Trends for all parameters were similar in patients across weight and BMI sub-categories.

CONCLUSION

In obese individuals, abdominal CT images reconstructed using ASiR provide diagnostic images with reduced image noise at lower radiation dose.

KEY POINTS

• CT images in obese adults are noisy, even with high radiation dose. • Newer iterative reconstruction techniques have theoretical advantages in obese patients. • Adaptive statistical iterative reconstruction should reduce image noise and radiation dose. • This has been proven in abdominopelvic CT images of obese patients.

Application of an M-line-based backprojected filtration algorithm to triple-cone-beam helical CT

To increase the scanning speed of cone-beam CT, a scanning configuration with three pairs of x-ray sources and panel detectors was proposed. In this paper, we apply the M-line-based backprojected filtration algorithm to this scanning configuration and propose a fast implementation for this algorithm. Compared with existing implementations, the advantages of our implementation are as follows: (1) it can directly reconstruct horizontal slices (i.e. the slices perpendicular to the rotation axis), without 3D interpolation; (2) it does not need to calculate the backprojection intervals for any point; (3) it has a high degree of parallelism and is suitable for acceleration on graphic processing units or other parallel systems.

Fast exact/quasi-exact FBP algorithms for triple-source helical cone-beam CT

Cardiac computed tomography (CT) has been improved over past years, but it still needs improvement for higher temporal resolution in the cases of high or irregular cardiac rates. Given successful applications of dual-source cardiac CT scanners, triple-source cone-beam CT seems a promising mode for cardiac CT. In this paper, we propose two filtered-backprojection algorithms for triple-source helical cone-beam CT. The first algorithm utilizes two families of filtering lines. These lines are parallel to the tangent of the scanning trajectory and the so-called L lines. The second algorithm utilizes two families of filtering lines tangent to the boundaries of the Zhao window and L lines, respectively, but it eliminates the filtering paths along the tangent of the scanning trajectory, thus reducing the required detector size greatly. The first algorithm is theoretically exact for r < 0.265R and quasi-exact for 0.265R <or= r < 0.495R, and the second algorithm is quasi-exact for r < 0.495R , where r and R denote the object radius and the trajectory radius, respectively. Both algorithms are computationally efficient. Numerical results are presented to verify and showcase the proposed algorithms.

A scheme for multisource interior tomography

Currently, x-ray computed tomography (CT) requires source scanning so that projections can be collected from various orientations for image reconstruction. Limited by the scanning time, the temporal resolution of CT is often inadequate when rapid dynamics is involved in an object to be reconstructed. To meet this challenge, here the authors propose a scheme of multisource interior tomography for ultrafast imaging that reconstructs a relatively small region of interest (ROI). Specifically, such a ROI is irradiated in parallel with narrow x-ray beams defined by many source-detector pairs for data acquisition. This ROI can be then reconstructed using the interior tomography approach. To demonstrate the merits of this approach, the authors report interior reconstruction from in vivo lung CT data at a much reduced radiation dose, which is roughly proportional to the ROI size. The results suggest a scheme for ultrafast tomography (such as with a limited number of sources and in a scanning mode) to shorten data acquisition time and to suppress motion blurring.

Exact image reconstruction with triple-source saddle-curve cone-beam scanning

In this paper, we propose an exact shift-invariant filtered backprojection (FBP) algorithm for triple-source saddle-curve cone-beam CT. In this imaging geometry, the x-ray sources are symmetrically positioned along a circle, and the trajectory of each source is a saddle curve. Then, we extend Yang's formula from the single-source case to the triple-source case. The saddle curves can be divided into four parts to yield four datasets. Each of them contains three data segments associated with different saddle curves, respectively. Images can be reconstructed on the planes orthogonal to the z-axis. Each plane intersects the trajectories at six points (or three points at the two ends) which can be used to define the filtering directions. Then, we discuss the properties of these curves and study the case of 2N+1 sources (N>or=2). A necessary condition and a sufficient condition are given to find efficient curves. Finally, we perform numerical simulations to demonstrate the feasibility of our triple-source saddle-curve approach. The results show that the triple-source geometry is advantageous for high temporal resolution imaging, especially important for cardiac imaging and small animal imaging.

Exact image reconstruction with triple-source saddle-curve cone-beam scanning

In this paper, we propose an exact shift-invariant filtered backprojection (FBP) algorithm for triple-source saddle-curve cone-beam CT. In this imaging geometry, the x-ray sources are symmetrically positioned along a circle, and the trajectory of each source is a saddle curve. Then, we extend Yang's formula from the single-source case to the triple-source case. The saddle curves can be divided into four parts to yield four datasets. Each of them contains three data segments associated with different saddle curves, respectively. Images can be reconstructed on the planes orthogonal to the z-axis. Each plane intersects the trajectories at six points (or three points at the two ends) which can be used to define the filtering directions. Then, we discuss the properties of these curves and study the case of 2N+1 sources (N>or=2). A necessary condition and a sufficient condition are given to find efficient curves. Finally, we perform numerical simulations to demonstrate the feasibility of our triple-source saddle-curve approach. The results show that the triple-source geometry is advantageous for high temporal resolution imaging, especially important for cardiac imaging and small animal imaging.