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Objective. We introduce a robust image reconstruction algorithm named residual-guided Golub–Kahan iterative reconstruction technique (RGIRT) designed for sparse-view computed tomography (CT), which aims at high-fidelity image reconstruction from a limited number of projection views. Approach. RGIRT utilizes an inner-outer dual iteration framework, with a flexible least square QR (FLSQR) algorithm implemented in the inner iteration and a restarted iterative scheme applied in the outer iteration. The inner FLSQR employs a flexible Golub–Kahan bidiagonalization method to reduce the size of the inverse problem, and a weighted generalized cross-validation method to adaptively estimate the regularization hyper-parameter. The inner iteration efficiently yields the intermediate reconstruction result, while the outer iteration minimizes the residual and refines the solution by using the result obtained from the inner iteration. Main results. The reconstruction performance of RGIRT is evaluated and compared to other reference methods (FBPConvNet, SART-TV, and FLSQR) using projection data from both numerical phantoms and real experimental Micro-CT data. The experimental findings, from testing various numbers of projection views and different noise levels, underscore the robustness of RGIRT. Meanwhile, theoretical analysis confirms the convergence of residual for our approach. Significance. We propose a robust iterative reconstruction algorithm for x-ray CT scans with sparse views, thereby shortening scanning time and mitigating excessive ionizing radiation exposure to small animals. [ABSTRACT FROM AUTHOR]

Sparse-view computed tomography (CT) holds great promise for speeding up data acquisition and reducing radiation dose in CT scans. Recent advances in reconstruction algorithms for sparse-view CT, such as iterative reconstruction algorithms, obtained high-quality image while requiring advanced computing power. Lately, deep learning (DL) has been widely used in various applications and has obtained many remarkable outcomes. In this paper, we propose a new method for sparse-view CT reconstruction based on the DL approach. The method can be divided into two steps. First, filter backprojection (FBP) was used to reconstruct the CT image from sparsely sampled sinogram. Then, the FBP results were fed to a DL neural network, which is a DenseNet and deconvolution-based network (DD-Net). The DD-Net combines the advantages of DenseNet and deconvolution and applies shortcut connections to concatenate DenseNet and deconvolution to accelerate the training speed of the network; all of those operations can greatly increase the depth of network while enhancing the expression ability of the network. After the training, the proposed DD-Net achieved a competitive performance relative to the state-of-the-art methods in terms of streaking artifacts removal and structure preservation. Compared with the other state-of-the-art reconstruction methods, the DD-Net method can increase the structure similarity by up to 18% and reduce the root mean square error by up to 42%. These results indicate that DD-Net has great potential for sparse-view CT image reconstruction. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM AUTHOR]

Background: The purpose of this study was to investigate the relative contributions of two proposed mechanisms, strength imbalance and impaired longitudinal muscle growth, to osseous and postural deformity in a rat model of brachial plexus birth palsy (BPBP). Methods: Thirty-two Sprague-Dawley rat pups were divided into four groups on the basis of surgical interventions to induce a strength imbalance, impaired growth, both a strength imbalance and impaired growth (a combined mechanism), and a sham condition in the left forelimb. Maximum passive external shoulder rotation angle (ERmax) was measured bilaterally at four and eight weeks postoperatively. After the rats were killed at eight weeks, the glenohumeral geometry (on microcomputed tomography) and shoulder muscle architecture properties were measured bilaterally. Results: Bilateral muscle mass and optimal length differences were greatest in the impaired growth and combined mechanism groups, which also exhibited >15° lower ERmax (p < 0.05; four weeks postoperatively), 14° to 18° more glenoid declination (p < 0.10), and 0.76 to 0.94 mm more inferior humeral head translation (p < 0.10) on the affected side. Across all four groups, optimal muscle length was significantly correlated with at least one osseous deformity measure for six of fourteen muscle compartments crossing the shoulder on the affected side (p < 0.05). In the strength imbalance group, the glenoid was 5° more inclined and the humeral head was translated 7.5% more posteriorly on the affected side (p < 0.05). Conclusions: Impaired longitudinal muscle growth and shoulder deformity were most pronounced in the impaired growth and combined mechanism groups, which underwent neurectomy. Strength imbalance was associated with osseous deformity to a lesser extent. Clinical Relevance: Treatments to alleviate shoulder deformity should address mechanical effects of both strength imbalance and impaired longitudinal muscle growth, with an emphasis on developing new treatments to promote growth in muscles affected by BPBP. [ABSTRACT FROM AUTHOR]

The hybrid spectral micro-computed tomography (CT) architecture integrates a conventional imaging chain and an interior spectral imaging chain, and has been proven to be an important development in spectral CT. The motivation for this study is to minimize X-ray exposure for hybrid spectral micro-CT using both simulated and experimental scan data while maintaining the spectral fidelity of the reconstruction. Three elements of the hybrid scan protocol are investigated: truncation of the interior spectral chain and the numbers of projections for each of the global and interior imaging chains. The effect of these elements is quantified by analyzing how each affects the reconstructed spectral accuracy. The results demonstrate that there is significant scope for reduction of radiation exposure in the hybrid scan protocol. It appears decreasing the number of conventional projections offers the most potential for exposure reduction, while further reduction is possible by decreasing the interior FOV and number of spectral projections. SCANNING 36:444-455, 2014. © 2014 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Purpose: Microbeam radiation therapy (MRT) is defined as the use of parallel, microplanar x-ray beams with an energy spectrum between 50 and 300 keV for cancer treatment and brain radiosurgery. Up until now, the possibilities of MRT have mainly been studied using synchrotron sources due to their high flux (100s Gy/s) and approximately parallel x-ray paths. The authors have proposed a compact x-ray based MRT system capable of delivering MRT dose distributions at a high dose rate. This system would employ carbon nanotube (CNT) field emission technology to create an x-ray source array that surrounds the target of irradiation. Using such a geometry, multiple collimators would shape the irradiation from this array into multiple microbeams that would then overlap or interlace in the target region. This pilot study demonstrates the feasibility of attaining a high dose rate and parallel microbeam beams using such a system. Methods: The microbeam dose distribution was generated by our CNT micro-CT scanner (100 µm focal spot) and a custom-made microbeam collimator. An alignment assembly was fabricated and attached to the scanner in order to collimate and superimpose beams coming from different gantry positions. The MRT dose distribution was measured using two orthogonal radiochromic films embedded inside a cylindrical phantom. This target was irradiated with microbeams incident from 44 different gantry angles to simulate an array of x-ray sources as in the proposed compact CNT-based MRT system. Finally, phantom translation in a direction perpendicular to the microplanar beams was used to simulate the use of multiple parallel microbeams. Results: Microbeams delivered from 44 gantry angles were superimposed to form a singlemicrobeam dose distribution in the phantom with a FWHM of 300 µm (calculated value was 290 µm). Also, during the multiple beam simulation, a peak to valley dose ratio of ~10 was found when the phantom translation distance was roughly 4x the beam width. The first prototype CNT-based x-ray tube dedicated to the development of compact MRT technology development was proposed and planned based on the preliminary experimental results presented here and the previous corresponding Monte Carlo simulations. Conclusions: The authors have demonstrated the feasibility of creating microbeam dose distributions at a high dose rate using a proposed compact MRT system. The flexibility of CNT field emission x-ray sources could possibly bring compact and low cost MRT devices to the larger research community and assist in the translational research of this promising new approach to radiation therapy. [ABSTRACT FROM AUTHOR]

Purpose: The size of field-of-view (FOV) of a microcomputed tomography (CT) system can be increased by offsetting the detector. The increased FOV is beneficial in many applications. All prior investigations, however, have been focused to the case in which the increased FOV after offset-detector acquisition can cover the transaxial extent of an object fully. Here, the authors studied a new problem where the FOV of a micro-CT system, although increased after offset-detector acquisition, still covers an interior region-of-interest (ROI) within the object. Methods: An interior-ROI-oriented micro-CT scan with an offset detector poses a difficult reconstruction problem, which is caused by both detector offset and projection truncation. Using the projection completion techniques, the authors first extended three previous reconstruction methods from offset-detector micro-CT to offset-detector interior micro-CT. The authors then proposed a novel method which combines two of the extended methods using a frequency split technique. The authors tested the four methods with phantom simulations at 9.4%, 18.8%, 28.2%, and 37.6% detector offset. The authors also applied these methods to physical phantom datasets acquired at the same amounts of detector offset from a customized micro-CT system. Results: When the detector offset was small, all reconstruction methods showed good image quality. At large detector offset, the three extended methods gave either visible shading artifacts or high deviation of pixel value, while the authors' proposed method demonstrated no visible artifacts and minimal deviation of pixel value in both the numerical simulations and physical experiments. Conclusions: For an interior micro-CT with an offset detector, the three extended reconstruction methods can perform well at a small detector offset but show strong artifacts at a large detector offset. When the detector offset is large, the authors' proposed reconstruction method can outperform the three extended reconstruction methods by suppressing artifacts and maintaining pixel values. [ABSTRACT FROM AUTHOR]

Spectral CT has proven an important development in biomedical imaging, and there have been several publications in the past years demonstrating its merits in pre-clinical and clinical applications. In 2012, Xu reported that near-term implementation of spectral micro-CT could be enhanced by a hybrid architecture: a narrow-beam spectral “interior” imaging chain integrated with a traditional wide-beam “global” imaging chain. This hybrid integration coupled with compressive sensing (CS)-based interior tomography demonstrated promising results for improved contrast resolution, and decreased system cost and radiation dose. The motivation for the current study is implementation and evaluation of the hybrid architecture with a first-of-its-kind hybrid spectral micro-CT system. Preliminary results confirm improvements in both contrast and spatial resolution. This technology is shown to merit further investigation and potential application in future spectral CT scanner design. [ABSTRACT FROM PUBLISHER]