Removing ring artifacts presents a significant challenge in x-ray computed tomography (CT) systems, particularly in those utilizing photon-counting detectors. To solve this problem, this study proposes the Inter-slice Complementarity Enhanced Ring Artifact Removal (ICE-RAR) algorithm, which is based on a learning-based approach. The variability and complexity of detector responses make it challenging to acquire enough paired data for training neural networks in real-world scenarios. To address this, the research first introduces a data simulation strategy that incorporates the characteristics of specific systems in accordance with the principles of ring artifact formation. Following this, a dual-branch neural network is designed, consisting of a global artifact removal branch and a central region enhancement branch, aimed at improving artifact removal, especially in the central region of interest where artifacts are more difficult to eliminate. Additionally, considering the independence of different detector element responses, the study proposes leveraging inter-slice complementarity to improve image restoration. The effectiveness of the central region reinforcement and inter-slice complementarity was confirmed through ablation experiments on simulated data. Both simulated and real-world results demonstrated that the ICE-RAR method effectively reduces ring artifacts while preserving image details. More importantly, by incorporating specific system characteristics into the data simulation process, models trained on simulated data can be directly applied to unseen real data, presenting significant potential for addressing ring artifact removal (RAR) issue in practical CT systems.
C-arm x-ray systems equipped with flat panel detectors (FPD) lack spectral and ultra-high-resolution (UHR) capabilities desired by physicians for image guided interventions (IGIs), for example to discriminate between and/or quantify different materials such as iodine and calcium, or in the visualization of very fine structures or devices used in interventional procedures. Photon counting detectors (PCDs) can introduce these capabilities to the interventional suite: In this work, we propose a new dagger-shaped PCD design tailored for IGIs to upgrade the imaging capabilities in the C-arm interventional system while preserving the functionality of the existing FPD and reducing the system cost compared to completely replacing the FPD with a large-area PCD. The design consists of two modules integrated together: One is a long-strip shape for narrow-beam spectral and UHR CT with full axial coverage, and one is rectangle-shaped for volume- and region-of-interest 2D and 3D spectral and UHR imaging. As a proof of concept, prototypes of each module were used to perform phantom and in vivo animal experiments. Results show the potential of the proposed design in discriminating between and quantifying iodine and calcium by leveraging the spectral information provided by PCDs. UHR 2D and 3D PCD images show the improved capabilities of the dagger PCD in delineating small blood vessels with improved contrast-to-noise ratios, as well as resolving fine structures such as stents commonly used in IGIs.
In this work, a unified framework was developed to jointly address scatter artifacts, detector nonuniformity-induced concentric artifacts, and beam hardening artifacts in C-arm photon counting detector (PCD) cone beam CT. By leveraging the energy-resolving capability of PCDs, a better estimation of the scattered photon signal was obtained via a photoelectric-Compton scattering decomposition. Next, detector nonuniformity and beam hardening artifacts were jointly corrected via a second-round projection domain pixel-wise material decomposition. Both phantom and in vivo animal results demonstrated that the proposed correction method generated high-quality and quantitative PCD cone beam CT images for image-guided interventions.
Existing clinical C-arm interventional x-ray systems equipped with flat panel detectors (FPDs) can generate fluoroscopic, angiographic, and cone-beam CT (CBCT) images with sufficient volumetric coverage for interventional imaging tasks. However, FPD-CBCT does not provide sufficient low-contrast detectability, resolution, or spectral imaging capability desired for certain interventional procedures. To overcome these limitations, a C-arm photon counting detector (PCD) CT prototype was developed by installing an interchangeable strip PCD on the C-arm gantry. The narrow z width of the PCD reduces detector cost and reduces scatter when paired with a narrow beam collimation. However, it does not provide sufficient volumetric coverage compared to the standard FPD. The purpose of this work was to develop a step-and-shoot data acquisition method to enlarge the effective z-coverage of the C-arm strip PCD-CT system. A total of 10 back-and-forth short-scan C-arm gantry rotations were used with image object translation. By using an Arduino board to process the x-ray-on pulse signals in real-time, a motorized patient table prototype was synchronized with the C-arm system such that it translates the object by the PCD width during the rest time in between gantry rotations. To evaluate whether this multisweep step-and-shoot acquisition mode can generate high-quality and volumetric PCD-CT images, experiments were performed using an anthropomorphic head phantom, and a stent. The multi-sweep step-and-shoot C-arm protocol resulted in volumetric PCD-CT images with lower image noise and improved low-contrast visualization over the FPD-CBCT in the head phantom, as well as improved visibility of small iodinated blood vessels using maximum intensity projections. Under an ultra-high-resolution PCD mode, the fine structures of the stent were visualized more clearly by the PCD-CT than the highest-available resolution provided by the FPD-CBCT. The multi-sweep step-and-shoot acquisition can therefore extend the z-coverage of the C-arm PCD-CT prototype by a factor of 10 to enable high-quality and volumetric C-arm PCD-CT images acquired with a narrow beam-narrow detector setup for image-guided interventions.
The purpose of this work is develop a novel multi-contrast chest x-ray radiography (MC-CXR) imaging system to enable the simultaneous generation of three mutually complementary x-ray contrast mechanisms to enhance the diagnostic performance of CXR for respiratory diseases. The developed grating-based MC-CXR system employs a scanning beam image acquisition scheme in which the patient table is translated at a speed of up to 9 cm/s. The system is capable of accomplishing MC-CXR imaging of an anthropomorphic chest phantom in under 4 seconds, with an air kerma and effective dose that are well below that of a conventional CXR exam.
Due to the subtle variations of energy response functions across photoconductive panels, photon counting detector CT are subject to severe banding artifacts. This work presents a physics based method to correct for these artifacts. It employs calibration objects with known thicknesses and composition to estimate the panel-specific response functions, which are used to concert the raw photon counting projection data of an arbitrary image object into acrylic- and aluminum-equivalent pathlengths. Experimental results show the method not only remove the banding artifacts but also address the beam hardening artifacts.
Gout is the most prevalent inflammatory arthritis found in men. A prompt diagnosis and early treatment of gout are crucial in preventing eventual functional impairment and reduction in comorbidities. In this work, the quantitative material information provided by a multi-contrast x-ray (MCXR) imaging acquisition is leveraged to develop a rapid, non-invasive, and low dose diagnostic method for gout detection and gout-pseudogout differentiation. This work establishes a theoretical foundation to demonstrate how a single-kV MCXR acquisition is capable of differentiating gout from pseudogout via a projection domain two-material decomposition. Experimental results from a benchtop MCXR system are presented. The imaging performance of the proposed MCXR technique is compared to dual-energy radiography to further validate the method.
A peculiar edge enhancement effect was observed when a PCD was operated under anti-coincidence mode and irradiated by high-flux x-rays to cause pulse pileups. The severity of this effect increases with the input flux level and completely disappears when the anti-coincidence mode is turned off. A theoretical analysis shows that this edge enhancement effect was jointly caused by the pulse pileup-induced count loss and the arbitration process used the anti-coincidence logic. Compared with pixels blocked by an edge, pixels immediately outside the edge has a much higher likelihood to win the arbitration when there are coincident x-rays.
This work reports the development of a C-arm photon counting detectors (PCD)-CT system for evaluating the potential clinical utility of PCD-CT for intraoperative imaging. A dual-threshold CdTe-based strip PCD was mounted on a Siemens Artis Zee C-arm interventional system. A new geometric calibration method was developed to correct for the geometric distortion of the C-arm system during rotation. Experimental results show that, under clinically relevant conditions, the C-arm PCD-CT system can reliably and reproducibly generate high quality MDCT-like images without any noticeable geometric distortion or banding artifact.
Endovascular procedures performed in the angio suite have gained considerable popularity for treatment of ischemic stroke as well as aneurysms. However, new intracranial hemorrhage (ICH) may develop during these procedures, and it is highly desirable to arm the angio suite with real-time and reliable ICH monitoring tools. Currently, angio suites are equipped with scintillator-based flat panel detector (FPD) imaging systems for both planar and cone beam CT (CBCT) imaging applications. However, the reliability of CBCT for ICH imaging is insufficient due to its poor low-contrast detectability compared with MDCT and lack of spectral imaging capability for differentiating between ICH, calcifications, and iodine staining from periprocedural contrast-enhanced imaging sequences. To preserve the benefits of the FPD for 2D imaging and certain high-contrast 3D imaging tasks while adding a high quality, quantitative, and affordable CT imaging capability to the angio room for intraoperative ICH monitoring, a hybrid detector system was developed that includes the existing FPD on the C-arm gantry and a strip photon-counting detector (PCD) that can be translated into the field-of-view for high quality PCD-CT imaging at a given brain section-of-interest. The hybrid system maintains the openness and ease of use of the C-arm system without the need to remodel the angio room and without installing a slidinggantry MDCT (aka Angio CT) with orders of magnitude higher costs. Additionally, the cost of the strip PCD is much less than the cost of a large-area PCD. To demonstrate the feasibility and potential benefits of the hybrid PCD-FPD system, a series of physical phantom studies, and human cadaver studies were performed at a gantry rotation speed (7 s) and radiation dose level that closely match those of clinical CBCT acquisitions. The experimental images of C-arm PCD-CT demonstrated MDCT-equivalent low-contrast detectability of PCD-CT and significantly reduced artifacts compared with FPD-based CBCT.
This Conference Presentation, "Impacts of pulse pileup, charge sharing, and anti-charge sharing on the noise power spectra of photon counting detectors: theoretical analysis and experimental demonstrations," was recorded at Medical Imaging 2020 held in Houston, Texas, United States.
Three-material decomposition is crucial for material quantification when more than two elemental materials, including a K-edge material, are presented in an image object. In principle, three-material decomposition requires a triple energy scan which cannot be directly accomplished using a conventional dual energy CT system. In this work, a new scheme to enable three-material decomposition by employing phase contrast CT was presented. When a grating interferometer is added, a conventional absorption dual energy CT system can be upgraded to a phase contrast dual energy CT system which provides an additional phase signal related to the real part of the refractive index of an image object, along with the absorption signal under two different x-ray spectra. In this work, a three-material decomposition method was proposed for the aforementioned dual energy phase contrast CT system. Physical experimental studies were performed on a benchtop x-ray Talbot-Lau interferometer system to validate the proposed method. A physical phantom, containing calcium and iodine inserts of known concentrations, was used as the image object. A rotation-rotation dual energy phase contrast CT scan was performed under 40 and 80 kVp tube potentials. For each view angle, a phase stepping procedure with five phase steps was performed. After the phase retrieval procedure and image reconstruction using the standard filtered-back projection, the solutions were decomposed into the calcium, iodine and water bases based on the proposed decomposition method. For all the solutions, the relative quantification errors of the concentrations were within 10%.
Virtual non-contrast (VNC) CT images derived from multi-energy CT data have demonstrated many valuable clinical applications. However, VNC CT has not yet established itself as a technology that can reliably replace the true non-contrast CT. One commonly observed phenomenon is an erroneous removal or reduction of calcium signal in VNC images. The purpose of this work is to develop a photon counting CT-based method to decouple the iodine signal from the calcium signal to achieve VNC CT imaging. Thanks to the energy resolving capability of the photon counting detector (PCD), a photon counting CT enables all single kV CT data to carry additional spectral information needed for VNC CT reconstruction. However, the energy discriminating capability of a real PCD system is far from ideal, which can severely degrade the fidelity of the encoded spectral information and the efficiency of the material decomposition. In this work, a physics-based model of the PCD energy response function was developed and experimentally validated. By leveraging this model, a method was developed to correct the distorted spectral information in the measured PCD energy bin data, allowing the true post image object spectrum to be estimated to accomplish accurate three-material decomposition and VNC CT reconstruction. Both numerical simulation and experimental results demonstrated that the proposed spectral distortion correction method can effectively improve the CT number accuracy of both iodine-containing vessels and calcium-containing bony structures in VNC CT images.
Iodine K-edge CT imaging utilizes the sudden increase in the attenuation coefficient of iodine when the x-ray energy exceeds the K-shell binding energy of iodine. Early works on K-edge CT used multiple K-edge filters to generate different quasi-monoenergetic spectra with mean energies that straddled the iodine K-edge, and then multiple projections acquired with these spectra were processed to enhance the sensitivity of imaging iodine. Recent developments in energy-resolving photon counting detector (PCD) technology offer the potential for single-shot K-edge CT imaging. However, the performance of PCD-based iodine K-edge CT is often limited by the relatively low energy of the iodine K-edge (33.2 keV) compared with the mean energy of a polychromatic spectrum used in CT. This work explored the potential of introducing an iodine beam filter to PCD-based iodine K-edge CT to improve its imaging performance. To optimize the beam filtration condition, a realistic energy response function of an experimental PCD system was used when calculating the Cramér-Rao Lower Bounds (CRLBs) of three-material (iodine, bone, and water) decomposition estimators for each filtration condition. Experimental studies with a benchtop PCD CT system were performed to confirm the CRLB results. Both theoretical and experimental results demonstrated that by using an optimized iodine filter, quantitative accuracy of material basis images was improved. Compared with a commercial dual-energy-CT system, the optimized experimental K-edge CT system effectively reduced residual iodine signal in the bone basis image and reduced residual bone signal in the water-basis image.
The sensitivity factor of a grating-based x-ray differential phase contrast (DPC) imaging system determines how much fringe shift can be observed for a given refraction angle. It is commonly believed that increasing the sensitivity factor will improve the signal-to-noise ratio (SNR) of the phase signal. However, this may not always be the case if the intrinsic phase wrapping effect is taken into consideration. In this work, a theoretical derivation is provided to quantify relationship between the sensitivity and SNR for a given refraction angle, exposure level, and grating based x-ray DPC system. The theoretical derivation shows that the expected phase signal is not always proportional to the sensitivity factor and may even decrease when the sensitivity factor becomes too large. The noise variance of the signal is not always solely dependent on the exposure level and fringe visibility but may become signal-dependent under certain circumstances. As a result, SNR of the phase signal does not always increase with higher sensitivity. Numerical simulation studies were performed to validate the theoretical models. Results show that when the fringe visibility and exposure level are fixed, there exists an optimal sensitivity factor which maximizes the SNR for a given refraction angle; further increase of the sensitivity factor may decrease the SNR.
KEYWORDS: Signal to noise ratio, Imaging systems, Error analysis, Modulation transfer functions, Signal detection, Photons, Numerical simulations, X-ray imaging
In 1963, Shaw applied Fourier analysis to the zero-frequency DQE and developed the frequency-dependent DQE or DQE(k) and made it clear that DQE(k) is applicable to every frequency level within the system bandwidth, including the zero frequency. Over time, especially after entering the modern era of digital x-ray imaging, the experimental measurement methods of DQE(k) (particularly the measurements of the NPS which is an important element in DQE(k)) have evolved, and some measurement methods may generate nonphysical NPS and DQE results at k=0. As a result, an experimental DQE(k) curve is often cut off at certain low frequency above zero. This work presents a new experimental method to deal with two challenges: severe NPS(k=0) underestimation due to polynomial-based background detrending; severe NPS(k=0) overestimation due to the presence of faint but non-negligible system drift. Based on a theoretical analysis of the impact of drift to the measured autocovariance function, the error introduced by drift can be isolated, and corresponding correction can be applied to NPS(k=0). Both numerical simulation with known ground truth and experimental studies demonstrated that the proposed method enables accurate DQE(k=0) measurement.
KEYWORDS: Signal to noise ratio, Computed tomography, Arteries, Sensors, Photon counting, Angiography, Signal detection, X-ray computed tomography, Spatial resolution, Head
Cerebral CT angiography (CTA) is widely used for the diagnosis of various cerebrovascular diseases, including strokes, vasculitis, aneurysms, and etc.2–4 For the diagnosis of ischemic strokes, the availability of high quality CTA images not only helps in identifying the presence/location of large vessel occlusion but also facilitates the assessment of collateral blood supply. As another example, accurate rendering of the superficial temporal arteries is valuable in identifying vessel inflammations induced by giant cell arteritis.5 While CTA is an established clinical gold standard for imaging large cerebral arteries and veins,1 an important challenge that currently remains for MDCT-based CTA is its limited performance in imaging small perforating arteries with a diameter below 0.5 mm.4 As a consequence, the relativley invasive artery biopsy procedure remains the current clinical gold standard for the diagnosis of giant cell arteritis.6 The use of indirect conversion energy integrating detectors puts intrinsic limit on the spatial resolution of MDCT, both in-plane and along the z direction. Severe partial volume averaging effect (PVE) and the preferential weighting of high energy photons7 are among major reasons for the relatively poor performance of MDCT-based CTA for imaging iodinated small vessels. Photon counting detector-based CT (PCD-CT) offers potential technological solutions to these challenges MDCT systems face for CTA. When compared to MDCT, the direct conversion design of PCD reduces limitations on both in-plane and through-plane spatial resolution, and the inherent equal weighting of high and low energy photons of PCD-CT systems offers an improvement in the CNR of iodinated vessels. The purpose of this work was to theoretically and experimentally study the potential impacts of the PCD-CT technology to an important component of CTA image package: the maximum intensity projection (MIP) image. MIP is a simple 3D image visualization method to display CTA data sets. Based on source images alone, it can be very challenging to evaluate occlusion conditions since most vessels extend to different z positions. In comparison, a MIP image that extracted information from a much longer z range can provide clearer evidence for an occlusion; in addition, it can effectively enhance the visibility of small collateral vessels. This work first derived the statistical properties of the MIP image, then analyzed how each of the benefits of PCD (improved z resolution; reduced noise autocovariance along z) propagates from the source CT images to the final MIP image. Finally, experiments were performed using a benchtop PCD-CT system and an anthropomorphic CTA phantom to showcase the significantly improved visibility of small perforating arteries.
In this work, the potential application of photon counting detector CT (PCD-CT) in intracranial hemorrhage (ICH) imaging was investigated. An experimental PCD-CT imaging system was constructed and optimized for the detection of low contrast intraparenchymal bleeding. The system uses a CdTe-based PCD that provides 51 cm axial coverage and excellent DQE performance. A customized anthropomorphic head phantom with a built-in ICH model was used to evaluate the performance of the PCD-CT system for the ICH detection task. The nominal contrast between the ICH model and brain parenchyma is 10 HU. The phantom was also scanned by a commercial multi-detector CT (MDCT) system to obtain gold standard images. For the sake of fair comparison, radiation dose level, tube potential, slice thickness, reconstruction pixel size were matched between the two CT systems. The nonprewhitening observer detectability index d' was used as the figure-of-merit for optimizing the detector binning mode and reconstruction kernel for the PCD-CT system. Compared with the gold-standard MDCT images, the optimized PCD-CT images demonstrated higher d0 value for the detection of the ICH model in the head phantom.
By integrating a grating-based interferometer with a clinical full field digital mammography (FFDM) system, a prototype multi-contrast (absorption, phase, and dark field) x-ray breast imaging system was developed in this work. Unlike previous benchtop-based multi-contrast x-ray imaging systems that usually have relatively long source-to-detector distance and vibration isolators or dampers for the interferometer, the FFDM hardware platform is subject to mechanical vibration and the constraint of compact system geometry. Current grating fabrication technology also imposes additional constraints on the design of the grating interferometer. Based on these technical constraints and the x-ray beam properties of the FFDM system, three gratings were designed and integrated with the FFDM system. When installing the gratings, no additional vibration damping device was used in order to test the robustness of multi-contrast imaging system against mechanical vibration. The measured visibility of the diffraction fringes was 23±3%, and two images acquired 60 minutes apart demonstrated good system reproducibility with no visible signal drift. Preliminary results generated from the prototype system demonstrate the multi-contrast imaging capability of the system. The three contrast mechanisms provide mutually complementary information of the phantom object. This prototype system provides a much needed platform for evaluating the true clinical utility of the multi-contrast x-ray imaging method for the diagnosis of breast cancer.
KEYWORDS: Photon counting, Sensors, Image processing, Interference (communication), X-rays, Modulation transfer functions, Signal detection, Cadmium, Systems modeling, X-ray imaging, Medical imaging, Single photon, X-ray detectors
Recent advances in single photon counting detectors (PCDs) are opening up new opportunities in medical imaging. However, the performance of PCDs is not flawless. Problems such as charge sharing may deteriorate the performance of PCD. This work studied the dependence of the signal and noise properties of a cadmium telluride (CdTe)-based PCD on the charge sharing effect and the anti-charge sharing (ACS) capability offered by the PCD. Through both serial and parallel cascaded systems analysis, a theoretical model was developed to trace the origin of charge sharing in CdTe-based PCD, which is primarily related to remote k-fluorescence re-absorption and spatial spreading of charge cloud. The ACS process was modeled as a sub-imaging state prior to the energy thresholding stage, and its impact on the noise power spectrum (NPS) of PCD can be qualitatively determined by the theoretical model. To validate the theoretical model, experimental studies with a CdTe-based PCD system (XC-FLITE X1, XCounter AB) was performed. Two x-ray radiation conditions, including an RQA-5 beam and a 40 kVp beam, were used for the NPS measurements. Both theoretical predictions and experimental results showed that ACS makes the NPS of the CdTe-based PCD flatter, which corresponds to reduced noise correlation length. The flatness of the NPS is further boosted by increasing the energy threshold or reducing the x-ray energy, both of which reduce the likelihood of registering multiple counts from the same incidenting x-ray photon.
The noise performance of grating-based differential phase contrast (DPC) imaging system is strongly dependent on the fringe visibility of the grating interferometer. Since the grating interferometer system is usually designed to be operated at a specific energy, deviation from that energy may lead to visibility loss and increased noise. By incorporating an energy-discriminating photon counting detector (PCD) into the system, photons with energies close to the operation energy of the interferometer can be selected, which offers the possibility of contrast-tonoise ratio (CNR) improvement. In our previous work, a singular value decomposition (SVD)-based rank one approximation method was developed to improve the CNR of DPC imaging. However, as the noise level and energy sensitivity of the interferometer may vary significantly from one energy bin to another, the signal and noise may not be separated well using the previously proposed method, therefore the full potential of the SVD method may not be achieved. This work presents a weighted SVD-based method, which maintains the noise reduction capability regardless of the similarity in the noise level across energy bins. The optimal weighting scheme was theoretically derived, and experimental phantom studies were performed to validate the theory and demonstrate the improved radiation dose efficiency of the proposed weighted SVD method.
In grating based multi-contrast x-ray imaging, signals of three contrast mechanisms, namely absorption contrast, differential phase contrast (DPC) and dark-field contrast, can be estimated from a single data acquisition with several phase steps. The extracted signals, N0 (related to absorption), N1 (related to dark-field) and φ (related to DPC) may be intrinsically biased. In this work, the biases of the extracted N0, N1 and φ from the well-known least square fitting method were theoretically derived. Furthermore, numerical simulation experiments were used to validate the derived theoretical formulae for the signal bias of all three contrast mechanisms. The theoretical predictions were in good agreement with the results of the simulations. The bias of the absorption contrast is zero. The signal bias for N1 is inversely proportional to the number of phase steps and to the average fringe visibility of the grating interferometer. The bias of φ is related to several parameters, including the total exposure, the fringe visibility produced by the interferometer system, and the ground truth of φ. The larger the exposure and fringe visibility, the smaller the bias of φ.
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