Cone-beam Geometry Research Articles

A gradient-based approach to fast and accurate head motion compensation in cone-beam CT.

Cone-beam computed tomography (CBCT) systems, with their flexibility, present a promising avenue for direct point-of-care medical imaging, particularly in critical scenarios such as acute stroke assessment. However, the integration of CBCT into clinical workflows faces challenges, primarily linked to long scan duration resulting in patient motion during scanning and leading to image quality degradation in the reconstructed volumes. This paper introduces a novel approach to CBCT motion estimation using a gradient-based optimization algorithm, which leverages generalized derivatives of the backprojection operator for cone-beam CT geometries. Building on that, a fully differentiable target function is formulated which grades the quality of the current motion estimate in reconstruction space. We drastically accelerate motion estimation yielding a 19-fold speed-up compared to existing methods. Additionally, we investigate the architecture of networks used for quality metric regression and propose predicting voxel-wise quality maps, favoring autoencoder-like architectures over contracting ones. This modification improves gradient flow, leading to more accurate motion estimation. The presented method is evaluated through realistic experiments on head anatomy. It achieves a reduction in reprojection error from an initial average of 3 mm to 0.61 mm after motion compensation and consistently demonstrates superior performance compared to existing approaches. The analytic Jacobian for the backprojection operation, which is at the core of the proposed method, is made publicly available. In summary, this paper contributes to the advancement of CBCT integration into clinical workflows by proposing a robust motion estimation approach that enhances efficiency and accuracy, addressing critical challenges in time-sensitive scenarios.

Enhancing cerebral vasculature analysis with pathlength-corrected 2D angiographic parametric imaging: A feasibility study.

2D angiographic parametric imaging (API) quantitatively extracts imaging biomarkers related to contrast flow and is conventionally applied to 2D digitally subtracted angiograms (DSA's). In the interventional suite, API is typically performed using 1-2 projection views and is limited by vessel overlap, foreshortening, and depth-integration of contrast motion. This work explores the use of a pathlength-correction metric to overcome the limitations of 2D-API: the primary objective was to study the effect of converting 3D contrast flow to projected contrast flow using a simulated angiographic framework created with computational fluid dynamics (CFD) simulations, thereby removing acquisition variability. The pathlength-correction framework was applied to in-silico angiograms, generating a reference (i.e., ground-truth) volumetric contrast distribution in four patient-specific intracranial aneurysm geometries. Biplane projections of contrast flow were created from the reference volumetric contrast distributions, assuming a cone-beam geometry. A Parker-weighted reconstruction was performed to obtain a binary representation of the vessel structure in 3D. Standard ray tracing techniques were then used to track the intersection of a ray from the focal spot with each voxel of the reconstructed vessel wall to a pixel in the detector plane. The lengths of each ray through the 3D vessel lumen were then projected along each ray-path to create a pathlength-correction map, where the pixel intensity in the detector plane corresponds to the vessel width along each source-detector ray. By dividing the projection sequences with this correction map, 2D pathlength-corrected in-silico angiograms were obtained. We then performed voxel-wise (3D) API on the ground-truth contrast distribution and compared it to pixel-wise (2D) API, both with and without pathlength correction for each biplane view. The percentage difference (PD) between the resultant API biomarkers in each dataset were calculated within the aneurysm region of interest (ROI). Intensity-based API parameters, such as the area under the curve (AUC) and peak height (PH), exhibited notable changes in magnitude and spatial distribution following pathlength correction: these now accurately represent conservation of mass of injected contrast media within each arterial geometry and accurately reflect regions of stagnation and recirculation in each aneurysm ROI. Improved agreement was observed between these biomarkers in the pathlength-corrected biplane maps: the maximum PD within the aneurysm ROI is 3.3% with pathlength correction and 47.7% without pathlength correction. As expected, improved agreement with ROI-averaged ground-truth 3D counterparts was observed for all aneurysm geometries, particularly large aneurysms: the maximum PD for both AUC and PH was 5.8%. Temporal parameters (mean transit time, MTT, time-to-peak, TTP, time-to-arrival, TTA) remained unaffected after pathlength correction. This study indicates that the values of intensity-based API parameters obtained with conventional 2D-API, without pathlength correction, are highly dependent on the projection orientation, and uncorrected API should be avoided for hemodynamic analysis. The proposed metric can standardize 2D API-derived biomarkers independent of projection orientation, potentially improving the diagnostic value of all acquired 2D-DSA's. Integration of a pathlength correction map into the imaging process can allow for improved interpretation of biomarkers in 2D space, which may lead to improved diagnostic accuracy during procedures involving the cerebral vasculature.

Accuracy of Electron Density Mapping of a Novel kVCBCT System Designed for Planning

A recently developed advanced kVCBCT system, designed for simulation and planning, includes improvements to the imaging panel and reconstruction technique, enabling more accurate electron density mapping than a typical CBCT. This study investigates the accuracy, limitations, and dosimetric impact of this new system. CBCT images were taken of both large (pelvis) and small (head) electron density phantoms with inserts ranging from lung (0.29) to cortical bone (1.69). Images were taken with several pre-set protocols with energies of 125 kVp and 140 kVp. The effects of longitudinal buildup (for scatter due to the cone-beam geometry) and blade position were also investigated. The HU values of each insert were measured over a small region of interest. Several electron density curves were generated - pelvis protocol on the large phantom, head protocol on the small phantom, and average - and imported into a treatment planning system. Dose calculation was performed using each curve and differences were observed. HU to electron density mapping was sensitive to the use of longitudinal buildup and blade position, with differences in the curves observed at both low and high electron densities, due to imager saturation effects not found in typical clinical scenarios. Subsequent studies used both longitudinal buildup and fully opened blades. Under these conditions, mapping was not sensitive to technique or phantom size at low electron densities. At higher values, the curves diverged, with the head protocol showing higher HU values and the pelvis protocol showing lower. The average curve matched very closely with the curve from our standard CT simulator. Dose calculation showed little dependence on the curve chosen, with max point dose differences of 1.2% between the pelvis and average scans, though most of the plan was <0.5% different. Results for the head protocol were similar. The system provides reliable HU values comparable to a CT simulator, though it is important to consider the effects of imager saturation by choosing appropriate scatter and collimation. The calibration is slightly sensitive to the choice of phantom size and beam energy, though these differences led to negligible (<0.5%) differences in dose calculation accuracy.

Grating designs for cone beam edge illumination X-ray phase contrast imaging: a simulation study.

Edge illumination is an emerging X-ray phase contrast imaging technique providing attenuation, phase and dark field contrast. Despite the successful transition from synchrotron to lab sources, the cone beam geometry of lab systems limits the effectiveness of using conventional planar gratings. The non-parallel incidence of X-rays introduces shadowing effects, worsening with increasing cone angle. To overcome this limitation, several alternative grating designs can be considered. In this paper, the effectiveness of three alternative designs is compared to conventional gratings using numerical simulations. Improvements in flux and contrast are discussed, taking into account practical considerations concerning the implementation of the designs.

Generating missing patient anatomy from partially acquired cone-beam computed tomography images using deep learning: a proof of concept

The patient setup technique currently in practice in most radiotherapy departments utilises on-couch cone-beam computed tomography (CBCT) imaging. Patients are positioned on the treatment couch using visual markers, followed by fine adjustments to the treatment couch position depending on the shift observed between the computed tomography (CT) image acquired for treatment planning and the CBCT image acquired immediately before commencing treatment. The field of view of CBCT images is limited to the size of the kV imager which leads to the acquisition of partial CBCT scans for lateralised tumors. The cone-beam geometry results in high amounts of streaking artifacts and in conjunction with limited anatomical information reduces the registration accuracy between planning CT and the CBCT image. This study proposes a methodology that can improve radiotherapy patient setup CBCT images by removing streaking artifacts and generating the missing patient anatomy with patient-specific precision. This research was split into two separate studies. In Study A, synthetic CBCT (sCBCT) data was created and used to train two machine learning models, one for removing streaking artifacts and the other for generating the missing patient anatomy. In Study B, planning CT and on-couch CBCT data from several patients was used to train a base model, from which a transfer of learning was performed using imagery from a single patient, producing a patient-specific model. The models developed for Study A performed well at removing streaking artifacts and generating the missing anatomy. The outputs yielded in Study B show that the model understands the individual patient and can generate the missing anatomy from partial CBCT datasets. The outputs generated demonstrate that there is utility in the proposed methodology which could improve the patient setup and ultimately lead to improving overall treatment quality.

New Advances in CT Dosimetry: The Planar Average Equilibrium Dose

Background: The basis for the current output dose measurement in CT is the computer tomography dose index (CTDI). Modern CT scanners with helical scanning modes, dosage modulation, array detectors, multiple slice planes, or cone-beam irradiation geometries are incompatible with the conventional methods for measuring CT dosimetric performance. The AAPM TG 111 study acknowledged the shortcomings of the CTDI methods and suggested a new method that uses a short conventional ion chamber instead of a pencil chamber and better characterizes the dose profile from contemporary CT scanners.&#x0D; &#x0D; Materials and Methods: Three different anatomical regions (head, chest, and abdomen) of clinical scan sequences were used to build and characterize an in-house phantom design. The equilibrium dosage in our phantom was estimated to determine whether the attenuation of the beam was the same as that of the CTDI phantom. The obtained measurements were compared to those of the CTDI dose estimates made using a conventional pencil chamber.&#x0D; &#x0D; Results: The proposed method allowed the assessment of the equilibrium dosage as well as the accumulation dose for any clinical scan length. By contrast, the CTDI approach can underestimate the dose by 25% to 35% according to our revised methodology&#x0D; &#x0D; Conclusion: The CTDI measurements could no longer be sufficient, and the informed CTDI tends to underestimate the dose provided.

Total Variation regularized reconstruction for enhancing the quality of few-view industrial computed tomography applied to image analysis and metrology

The few-view image reconstruction problem is one of the challenging research areas in industrial Computed Tomography (CT). On the one hand, acquiring enough data for reconstruction leads to a longer scanning time, which may not be applicable in industrial CT. On the other hand, reconstructing under-sampled data leads to artifacts and inaccurate image analysis. To get a usable reconstruction for image analysis, from the insufficient data caused by quick cone beam CT scans, we use a Total Variation (TV) regularized optimization problem. A split Bregman implementation is used to solve the TV regularized CT reconstruction problem. To evaluate the quality of the few-view reconstruction produced by the split Bregman, we perform gray value analysis and porosity analysis. The comparison is done against the established reconstruction algorithms OSSART and FDK approximate formula, using real and realistically simulated CT data in cone beam geometry.

Detailed analysis of the interference patterns measured in lab-based X-ray dual-phase grating interferometry through wave propagation simulation.

In this work, we analyze the interference patterns measured in lab-based dual-phase grating interferometry and for the first time explain the spatial dependencies of the measured interference patterns and the large visibility deviations between the theoretical prediction and the experimental results. To achieve this, a simulator based on wave propagation is developed. This work proves that the experimental results can be simulated with high accuracy by including the effective grating thickness profile induced by the cone-beam geometry, the measured detector response function and a non-ideal grating shape. With the comprehensive understanding of dual-phase grating interferometry, this provides the foundations for a more efficient and accurate algorithm to retrieve sample's structure information, and the realistic simulator is a useful tool for optimizing the set-up.

MOGNO, the nano and microtomography beamline at Sirius, the Brazilian synchrotron light source

The MOGNO beamline is a high-energy imaging beamline dedicated to in situ and operando experiments in heterogeneous and hierarchical samples, and one of the beamlines of the first phase of SIRIUS, the 4th generation storage ring at the LNLS. The beamline is currently under commissioning and will operate at energies of 21.5, 39.0 and 67.7 keV, using as primary source a 3.2T permanent magnet dipole, with critical energy of 19.15 keV. The beam is demagnified down to a nanometric focal spot (≈120 nm) using a set of three elliptical mirrors, which introduces a divergence and, hence, the beamline operates in a cone beam geometry with variable field-of-view (FoV between 150 µm to 85 mm) and spatial resolution (≈120 nm to 55 |am). These conditions are reached with two end-stations, the nanotomography and the microtomography stations. A high-Z photon counting detector, with detection area of ≈85 x 85 mm2, will serve for both the nano and micro-station, but the beamline will also count on an indirect detection system based on a sCMOS camera and a macroscope.

Effect of cone-beam CT detector size and projection geometry on scatter-induced image noise

<h3>Objective</h3> The aim of this study was to evaluate the effect of detector size with different projection geometries on scatter-induced image noise in cone beam computed tomography (CBCT). <h3>Study Design</h3> A polymethyl methacrylate phantom containing air and aluminum underwent CBCT scanning positioned in the center of the FOV. Images were acquired with the PaX-i3D Green Premium (Vatech, Korea), which has a narrow vertical detector with off-axis projection geometry and multiple consecutive rotations for small and medium FOVs; the OP300 3D Maxio (Instrumentarium Dental, Tuusula, Finland), with aligned projection geometry for small FOV, and off-axis geometry for medium FOV; and the Promax 3D Max (Planmeca, Helsinki, Finland), which has aligned geometry for small and medium FOVs. Scans were performed using small and medium FOVs, combining tube voltages and tube currents to maintain a fixed normalized dose-area product. Signal difference-to-noise ratio (SDNR) was calculated on two-dimensional projection images and compared using one-way ANOVA with post hoc Tukey tests (α =0.05) between CBCT units. <h3>Results</h3> For small FOVs, Promax showed the highest SDNR compared to OP300 and PaX-i3D, with the difference being statistically significant (p < 0.0001). OP300 exhibited significantly higher SDNR values than PaX-i3D (p < 0.0001). For medium FOVs, Promax had significantly higher SDNR than OP300 and PaX-i3D (p < 0.0001), and no difference was discovered between OP300 and PaX-i3D. Therefore, Promax had the lowest scatter-induced image noise since it has aligned projection geometry in small and medium FOV sizes. For OP300, which has an off-axis geometry, the scatter-induced image noise with the medium FOV was comparable to PaX-i3D. <h3>Conclusion</h3> Reducing the active area of the detector does not result in fewer scattered photons reaching the detector, as it needs more rotations to capture all the projections. Moreover, in off-axis projections there is a lateral off-set of the detector, which results in the center of the FOV being positioned in the edges of the projection images. <b>Statement of Ethical Review</b> Ethical review was sought and study was exempted from ethical review

Effect of subject motion and gantry rotation speed on image quality and dose delivery in CT-guided radiotherapy.

To investigate the effects of subject motion and gantry rotation speed on computed tomography (CT) image quality over a range of image acquisition speeds for fan-beam (FB) and cone-beam (CB) CT scanners, and quantify the geometric and dosimetric errors introduced by FB and CB sampling in the context of adaptive radiotherapy. Images of motion phantoms were acquired using four CT scanners with gantry rotation speeds of 0.5s/rotation (denoted FB-0.5), 1.9s/rotation (FB-1.9), 16.6s/rotation (CB-16.6), and 60.0s/rotation (CB-60.0). A phantom presenting various tissue densities undergoing motion with 4-s period and ranging in amplitude from ±0.5 to ±10.0mm was used to characterize motion artifacts (streaks), motion blur (edge-spread function, ESF), and geometric inaccuracy (excursion of insert centroids and distortion of known shape). An anthropomorphic abdomen phantom undergoing ±2.5-mm motion with 4-s period was used to simulate an adaptive radiotherapy workflow, and relative geometric and dosimetric errors were compared between scanners. At ±2.5-mm motion, phantom measurements demonstrated mean±SD ESF widths of 0.6±0.0, 1.3±0.4, 2.0±1.1, and 2.9±2.0mm and geometric inaccuracy (excursion) of 2.7±0.4, 4.1±1.2, 2.6±0.7, and 2.0±0.5mm for the FB-0.5, FB-1.9, CB-16.6, and CB-60.0 scanners, respectively. The results demonstrated nonmonotonic trends with scanner speed for FB and CB geometries. Geometric and dosimetric errors in adaptive radiotherapy plans were largest for the slowest (CB-60.0) scanner and similar for the three faster systems (CB-16.6, FB-1.9, and FB-0.5). Clinically standard CB-60.0 demonstrates strong image quality degradation in the presence of subject motion, which is mitigated through faster CBCT or FBCT. Although motion blur is minimized for FB-0.5 and FB-1.9, such systems suffer from increased geometric distortion compared to CB-16.6. Each system reflects tradeoffs in image artifacts and geometric inaccuracies that affect treatment delivery/dosimetric error and should be considered in the design of next-generation CT-guided radiotherapy systems.

Cone-Beam Angle Dependency of 3D Models Computed from Cone-Beam CT Images.

Cone-beam dental CT can provide high-precision 3D images of the teeth and surrounding bones. From the 3D CT images, 3D models, also called digital impressions, can be computed for CAD/CAM-based fabrication of dental restorations or orthodontic devices. However, the cone-beam angle-dependent artifacts, mostly caused by the incompleteness of the projection data acquired in the circular cone-beam scan geometry, can induce significant errors in the 3D models. Using a micro-CT, we acquired CT projection data of plaster cast models at several different cone-beam angles, and we investigated the dependency of the model errors on the cone-beam angle in comparison with the reference models obtained from the optical scanning of the plaster models. For the 3D CT image reconstruction, we used the conventional Feldkamp algorithm and the combined half-scan image reconstruction algorithm to investigate the dependency of the model errors on the image reconstruction algorithm. We analyzed the mean of positive deviations and the mean of negative deviations of the surface points on the CT-image-derived 3D models from the reference model, and we compared them between the two image reconstruction algorithms. It has been found that the model error increases as the cone-beam angle increases in both algorithms. However, the model errors are smaller in the combined half-scan image reconstruction when the cone-beam angle is as large as 10 degrees.

An In-House Cone-Beam Tomographic Reconstruction Package for Laboratory X-ray Phase-Contrast Imaging

Phase-contrast, and in general, multi-modal, X-ray micro-tomography is proven to be very useful for low-density, low-attention samples enabling much better contrast than its attenuation-based pendant. Therefore, it is increasingly applied in bio- and life sciences primarily dealing with such samples. Although there is a plethora of literature regarding phase-retrieval algorithms, access to implementations of those algorithms is relatively limited and very few packages combining phase-retrieval methods with the full tomographic reconstruction pipeline are available. This is especially the case for laboratory-based phase-contrast imaging typically featuring cone-beam geometry. We present here an in-house cone-beam tomographic reconstruction package for laboratory X-ray phase-contrast imaging. It covers different phase-contrast techniques and phase retrieval methods. The paper explains their implementation and integration in the filtered back projection chain. Their functionality and efficiency will be demonstrated through applications on a few dedicated samples.

A new weighting scheme for arc based circle cone-beam CT reconstruction.

In this paper, we present an arc based fan-beam computed tomography (CT) reconstruction algorithm by applying Katsevich's helical CT image reconstruction formula to 2D fan-beam CT scanning data. Specifically, we propose a new weighting function to deal with the redundant data. Our weighting function ϖ(x_,λ) is an average of two characteristic functions, where each characteristic function indicates whether the projection data of the scanning angle contributes to the intensity of the pixel x_. In fact, for every pixel x_, our method uses the projection data of two scanning angle intervals to reconstruct its intensity, where one interval contains the starting angle and another contains the end angle. Each interval corresponds to a characteristic function. By extending the fan-beam algorithm to the circle cone-beam geometry, we also obtain a new circle cone-beam CT reconstruction algorithm. To verify the effectiveness of our method, the simulated experiments are performed for 2D fan-beam geometry with straight line detectors and 3D circle cone-beam geometry with flat-plan detectors, where the simulated sinograms are generated by the open-source software "ASTRA toolbox." We compare our method with the other existing algorithms. Our experimental results show that our new method yields the lowest root-mean-square-error (RMSE) and the highest structural-similarity (SSIM) for both reconstructed 2D and 3D fan-beam CT images.

Marker trajectory assessment in optical cone beam computed tomography scanner geometry

Measured trajectories of markers on vessel wall and beads on a plumb are compared with calculated trajectories for transmission images obtained with Vista16™ optical cone beam scanner. Effective pixel size was 0.11 mm. An algorithm was developed to measure trajectories for the plumb line phantom and a semi-automatic version was required for the gel filled vessels due to overlap of markers and seam projections at maximum lateral positions. It was found that for 15 cm diameter vessels, the vessel edge was not visible due to divergence in cone beam geometry. Accounting for this effect was necessary in order to remove artefacts from calculated vessel trajectory. Displacement differences were found to be less than 0.1 mm for the plumb line, 0.3 mm for a beads and 1 mm for markers on gel filled vessel. Minimization of the vessel marker trajectory deviation will provide a more accurate approach to refractive index optimization. No optical aberrations were detected from the trajectory analysis and manufacturer scanner alignment and geometrical calibrations were independently verified.

Retrieval of 3D information in X-ray dark-field imaging with a large field of view

X-ray dark-field imaging is a widely researched imaging technique, with many studies on samples of very different dimensions and at very different resolutions. However, retrieval of three-dimensional (3D) information for human thorax sized objects has not yet been demonstrated. We present a method, similar to classic tomography and tomosynthesis, to obtain 3D information in X-ray dark-field imaging. Here, the sample is moved through the divergent beam of a Talbot–Lau interferometer. Projections of features at different distances from the source seemingly move with different velocities over the detector, due to the cone beam geometry. The reconstruction of different focal planes exploits this effect. We imaged a chest phantom and were able to locate different features in the sample (e.g. the ribs, and two sample vials filled with water and air and placed in the phantom) to corresponding focal planes. Furthermore, we found that image quality and detectability of features is sufficient for image reconstruction with a dose of 68 μSv at an effective pixel size of 0.357 times {0.357},mathrm{mm}^{2}. Therefore, we successfully demonstrated that the presented method is able to retrieve 3D information in X-ray dark-field imaging.

Virtual speckle-based X-ray phase-contrast and dark-field imaging with digital phantoms

We demonstrate two versatile, flexible, and accurate frameworks based on numerical and Monte Carlo approaches to simulate the X-ray speckle-based (SBI) technique for lab-based systems. The established tools can reproduce experimental setups in a cone-beam geometry and with polychromatic sources. Furthermore, they are computationally efficient to enable a fast virtual multi-modal tomography of digitized inhomogeneous phantoms. The proposed methods were evaluated and validated by analytical and experimental data for various samples. The Monte Carlo approach provides a realistic and accurate simulation, which is useful in diffuser design and dosimetry studies, while the numerical method is very efficient for parametric and tomographic studies. These approaches will be used for the optimization of lab-based X-ray SBI setups and generating sample images for enhancing phase retrieval algorithms.

A convolutional neural network for estimating cone-beam CT intensity deviations from virtual CT projections

Extending cone-beam CT (CBCT) use toward dose accumulation and adaptive radiotherapy (ART) necessitates more accurate HU reproduction since cone-beam geometries are heavily degraded by photon scatter. This study proposes a novel method which aims to demonstrate how deep learning based on phantom data can be used effectively for CBCT intensity correction in patient images. Four anthropomorphic phantoms were scanned on a CBCT and conventional fan-beam CT system. Intensity correction is performed by estimating the cone-beam intensity deviations from prior information contained in the CT. Residual projections were extracted by subtraction of raw cone-beam projections from virtual CT projections. An improved version of U-net is utilized to train on a total of 2001 projection pairs. Once trained, the network could estimate intensity deviations from input patient head and neck raw projections. The results from our novel method showed that corrected CBCT images improved the (contrast-to-noise ratio) with respect to uncorrected reconstructions by a factor of 2.08. The mean absolute error and structural similarity index improved from 318 HU to 74 HU and 0.750 to 0.812 respectively. Visual assessment based on line-profile measurements and difference image analysis indicate the proposed method reduced noise and the presence of beam-hardening artefacts compared to uncorrected and manufacturer reconstructions. Projection domain intensity correction for cone-beam acquisitions of patients was shown to be feasible using a convolutional neural network trained on phantom data. The method shows promise for further improvements which may eventually facilitate dose monitoring and ART in the clinical radiotherapy workflow.

Radiation dose estimation for pencil beam X-ray luminescence computed tomography imaging.

Pencil beam X-ray luminescence computed tomography (XLCT) imaging provides superior spatial resolution than other imaging geometries like sheet beam and cone beam geometries. However, the pencil beam geometry suffers from long scan times, resulting in concerns overdose which discourages the use of pencil beam XLCT. The dose deposited in pencil beam XLCT imaging was investigated to estimate the dose from one angular projection scan with three different X-ray sources. The dose deposited in a typical small animal XLCT imaging was investigated. A Monte Carlo simulation platform, GATE (Geant4 Application for Tomographic Emission) was used to estimate the dose from one angular projection scan of a mouse leg model with three different X-ray sources. Dose estimations from a six angular projection scan by three different X-ray source energies were performed in GATE on a mouse trunk model composed of muscle, spine bone, and a tumor. With the Sigray source, the bone marrow of mouse leg was estimated to have a radiation dose of 44 mGy for a typical XLCT imaging with six angular projections, a scan step size of 100 micrometers, and 106 X-ray photons per linear scan. With the Sigray X-ray source and the typical XLCT scanning parameters, we estimated the dose of spine bone, muscle tissues, and tumor structures of the mouse trunk were 38.49 mGy, 15.07 mGy, and 16.87 mGy, respectively. Our results indicate that an X-ray benchtop source (like the X-ray source from Sigray Inc.) with high brilliance and quasi-monochromatic properties can reduce dose concerns with the pencil beam geometry. Findings of this work can be applicable to other imaging modalities like X-ray fluorescence computed tomography if the imaging protocol consists of the pencil beam geometry.

Tetrahedron beam imaging with a multi-pixel thermionic emission X-ray source and a photon-counting detector: A benchtop experimental study.

A tetrahedron beam (TB) X-ray system with a linear X-ray source array and a linear detector array positioned orthogonal to each other may overcome the X-ray scattering problem of traditional cone-beam X-ray systems. We developed a TB imaging benchtop system using a linear array X-ray source to demonstrate the principle and benefits of TB imaging. A multi-pixel thermionic emission X-ray (MPTEX) source with 48 focal spots in 4-mm spacing was developed in-house. The X-ray beams are collimated to a stack of fan beams that are converged to a 6-mm wide multi-row photon-counting detector (PCD). The data collected with a sequential scan of the sources at a fixed view angle were synthesized to a 2D radiography image by a shift-and-add algorithm. The data collected with a full rotation of the system were reconstructed into 3D TB CT (TBCT) images using an Feldkamp, Davis, and Kress (FDK)-based computed tomography (CT) algorithm modified for the TB geometry. With an 18.8-cm long source array and a 35-cm long detector array, the TB benchtop system provides a 25-cm cross-sectional and 8-cm axial field of view (FOV). The scatter-to-primary ratio (SPR) was approximately 17% for TB, as compared with 120% for cone beam geometry. The TBCT system enables reconstructions in two-dimensional radiography and three-dimensional volumetric CT. The TBCT images were free of "cupping" artifacts and have similar image quality as diagnostic helical CT. A TB imaging benchtop imaging system was successfully developed with MPTEX source and PCD. Phantom and animal cadaver imaging demonstrated that the TB system can produce satisfactory radiographic X-ray images and 3D CT images with image quality comparable to diagnostic helical CTs.