Reconstruction of Sparse-View X-ray Computed Tomography Based on Adaptive Total Variation Minimization

Sparse-view reconstruction has garnered significant interest in X-ray computed tomography (CT) imaging owing to its ability to lower radiation doses and enhance detection efficiency. Among current methods for sparse-view CT reconstruction, an algorithm utilizing iterative reconstruction based on full variational regularization demonstrates good performance. The optimized direction and number of computations for the gradient operator of the regularization term play a crucial role in determining not only the reconstructed image quality but also the convergence speed of the iteration process. The conventional TV approach solely accounts for the vertical and horizontal directions of the two-dimensional plane in the gradient direction. When projection data decrease, the edges of the reconstructed image become blurred. Exploring too many gradient directions for TV terms often comes at the expense of more computational costs. To enhance the balance of computational cost and reconstruction quality, this study suggests a novel TV computation model that is founded on a four-direction gradient operator. In addition, selecting appropriate iteration parameters significantly impacts the quality of the reconstructed image. We propose a nonparametric control method utilizing the improved TV approach as a solution to the tedious manual parameter optimization issue. The relaxation parameters of projection onto convex sets (POCS) are determined according to the scanning number and numerical proportion of the projection data; according to the image error before and after iterations, the gradient descent step of the TV item is adaptively adjusted. Compared with several representative iterative reconstruction algorithms, the experimental results show that the algorithm can effectively preserve edges and suppress noise in sparse-view CT reconstruction.

X-ray Single Exposure Imaging and Image Processing of Objects with High Absorption Ratio

The dynamic range of an X-ray digital imaging system is very important when detecting objects with a high absorption ratio. In this paper, a ray source filter is used to filter the low-energy ray components which have no penetrating power to the high absorptivity object to reduce the X-ray integral intensity. This enables the effective imaging of the high absorptivity objects and avoids the image saturation of low absorptivity objects, thus achieving single exposure imaging of high absorption ratio objects. However, this method will reduce the image contrast and weaken the image structure information. Therefore, this paper proposes a contrast enhancement method for X-ray images based on Retinex. Firstly, based on Retinex theory, the multi-scale residual decomposition network decomposes the image into an illumination component and a reflection component. Then, the contrast of the illumination component is enhanced through the U-Net model with the global-local attention mechanism, and the reflection component is enhanced in detail using the anisotropic diffused residual dense network. Finally, the enhanced illumination component and the reflected component are fused. The results show that the proposed method can effectively enhance the contrast in X-ray single exposure images of the high absorption ratio objects, and can fully display the structure information of images on devices with low dynamic range.

Interior Reconstruction from Truncated Projection Data in Cone-beam Computed Tomography

The interior reconstruction of completely truncated projection data is a frontier research hotspot in cone-beam computed tomography (CBCT) application. It is difficult to find a method with acceptable accuracy and high efficiency to solve it. Based on the simplified algebraic reconstruction technique (S-ART) algorithm and the filtered back projection (FBP) algorithm with the new filter, an efficient and feasible interior reconstruction algorithm is proposed in this paper. The algorithm uses the S-ART algorithm to quickly recover the complete projection data and then uses the new ramp filter which can suppress the high-frequency noise in the projection data to filter the recovered complete projection data. Finally, the interior reconstructed images are obtained by back projection. The computational complexity of the proposed algorithm is close to that of the FBP algorithm for the reconstruction of the whole object, and the reconstructed image quality is acceptable, which provides an effective method for interior reconstruction in CBCT. Simulation results show the effectiveness of the method.

Microwave ablation of multifocal primary liver cancer guided by real-time 3.0T MRI

OBJECTIVE

To investigate the feasibility and efficacy of real-time 3.0 T magnetic resonance imaging (MRI) guided percutaneous microwave ablation (MWA) in the treatment of multifocal liver cancer.

METHODS

A total of 76 lesions in 26 patients with multifocal liver cancer who underwent 3.0 T MRI-guided microwave ablation in our hospital from April 2020 to April 2022 were retrospectively analyzed. The technical success rate, average operation time, average ablation time, and complications were evaluated. The upper abdomen was reviewed by pre- and post-contrast enhanced MRI scan every 1 months after the operation. The short-term curative effect was evaluated according to the modified Response Evaluation Criteria in Solid Tumors (mRECIST) criteria (2020 version), and the local control rate was calculated.

RESULTS

All 76 lesions were successfully operated. The technical success rate was 100%, the average operation time was 103.58 ± 18.57 min, the average ablation time of a single lesion was 11.00 ± 4.05 min, and the average ablation power was 43.03 ± 4.45 W. There were no serious complications such as massive bleeding, liver failure, and infection after the operation, except in one case with a small amount of pleural effusion and one case with right upper abdominal pain. The average follow-up time was 13.88 ± 6.62 months. One patient died due to liver failure, and one lesion developed a local recurrence. The local control rate was 98.7%.

CONCLUSIONS

MWA of multifocal liver cancer guided by real-time 3.0 T MRI is a safe and feasible technique and has excellent short-term efficacy.

High-dynamic-range micro-CT for nondestructive testing of titanium 3D-printed medical components

Purpose: Industrial microcomputed tomography (micro-CT) scanners are suitable for nondestructive testing (NDT) of metal, 3D-printed medical components. Typically, these scanners are equipped with high-energy sources that require heavy shielding and costly infrastructure to operate safely, making routine NDT of medical components prohibitively expensive. Alternatively, fixed-current, low-cost x-ray units could be implemented to perform CT-based NDT of 3D-printed medical parts in a subset of cases, if there is sufficient x-ray transmission for the CT reconstruction. A lack of signal-caused by areas of high attenuation in two-dimensional-projection images of metal objects-leads to artifacts that can make an image-based NDT unreliable. We present the implementation of a dual-exposure technique devised to extend the dynamic range (DR) of a commercially available CT scanner equipped with a low-cost low-energy (80 kV) x-ray unit, increasing the signal-to-noise ratio of highly attenuated areas for NDT of 3D-printed medical components. Approach: Our high-dynamic-range CT (HDR-CT) technique adequately combines projection images acquired at two exposure levels by modifying the integration times of each protocol. We evaluate the performance and limitations of this HDR-CT technique by imaging a series of titanium-alloy test-samples. One of the test-samples was a resolution and conspicuity phantom designed to assess the improvements in void visualization of the proposed methodology. The other test-samples were four porous cylinders, 17 × 40    mm , with 60%, 70%, 80%, and 90% nominal internal porosities. Results: Our HDR-CT technique adequately combines projection images acquired at two exposure levels by modifying the integration times of each protocol. Our results demonstrate that the 12-bit native DR of the CT scanner was increased to effective values of between 14 and 16 bits. Conclusions: The HDR-CT reconstructions showed improved contrast-to-noise and void conspicuity, when compared with conventional CT scans. This extension of DR has the potential to improve defect visualization during NDT of medium-size, titanium-alloy, 3D-printed medical components.

Statistical iterative spectral CT imaging method based on blind separation of polychromatic projections

Spectral computed tomography (CT) can provide narrow-energy-width reconstructed images, thereby suppressing beam hardening artifacts and providing rich attenuation information for component characterization. We propose a statistical iterative spectral CT imaging method based on blind separation of polychromatic projections to improve the accuracy of narrow-energy-width image decomposition. For direct inversion in blind scenarios, we introduce the system matrix into the X-ray multispectral forward model to reduce indirect errors. A constrained optimization problem with edge-preserving regularization is established and decomposed into two sub-problems to be alternately solved. Experiments indicate that the novel algorithm obtains more accurate narrow-energy-width images than the state-of-the-art method.

Gradient-based and wavelet-based compressed sensing approaches for highly undersampled tomographic datasets

Electron tomography is widely employed for the 3D morphological characterization at the nanoscale. In recent years, there has been a growing interest in analytical electron tomography (AET) as it is capable of providing 3D information about the elemental composition, chemical bonding and optical/electronic properties of nanomaterials. AET requires advanced reconstruction algorithms as the datasets often consist of a very limited number of projections. Total variation (TV)-based compressed sensing approaches were shown to provide high-quality reconstructions from undersampled datasets, but staircasing artefacts can appear when the assumption about piecewise constancy does not hold. In this paper, we compare higher-order TV and wavelet-based approaches for AET applications and provide an open-source Python toolbox, Pyetomo, containing 2D and 3D implementations of both methods. A highly sampled STEM-HAADF dataset of an Er-doped porous Si sample and a heavily undersampled STEM-EELS dataset of a Ge-rich GeSbTe (GST) thin film annealed at 450°C are used to evaluate the performance of the different approaches. We show that polynomial annihilation with order 3 (HOTV₃) and the Bior4.4 wavelet outperform the classical TV minimization and the related Haar wavelet.

Multi-exposure X-ray image fusion quality evaluation based on CSF and gradient amplitude similarity

Due to the limitation of dynamic range of the imaging device, the fixed-voltage X-ray images often produce overexposed or underexposed regions. Some structure information of the composite steel component is lost. This problem can be solved by fusing the multi-exposure X-ray images taken by using different voltages in order to produce images with more detailed structures or information. Due to the lack of research on multi-exposure X-ray image fusion technology, there is no evaluation method specially for multi-exposure X-ray image fusion. For the multi-exposure X-ray fusion images obtained by different fusion algorithms may have problems such as the detail loss and structure disorder. To address these problems, this study proposes a new multi-exposure X-ray image fusion quality evaluation method based on contrast sensitivity function (CSF) and gradient amplitude similarity. First, with the idea of information fusion, multiple reference images are fused into a new reference image. Next, the gradient amplitude similarity between the new reference image and the test image is calculated. Then, the whole evaluation value can be obtained by weighting CSF. In the experiments of MEF Database, the SROCC of the proposed algorithm is about 0.8914, and the PLCC is about 0.9287, which shows that the proposed algorithm is more consistent with subjective perception in MEF Database. Thus, this study demonstrates a new objective evaluation method, which generates the results that are consistent with the subjective feelings of human eyes.

Spectral CT imaging method based on blind separation of polychromatic projections with Poisson prior

The linear reconstruction of narrow-energy-width projections can suppress hardening artifacts in conventional computed tomography (CT). We develop a spectral CT blind separation algorithm for obtaining narrow-energy-width projections under a blind scenario where the incident spectra are unknown. The algorithm relies on an X-ray multispectral forward model. Based on the Poisson statistical properties of measurements, a constrained optimization problem is established and solved by a block coordinate descent algorithm that alternates between nonnegative matrix factorization and Gauss-Newton algorithm. Experiments indicate that the decomposed projections conform to the characteristics of narrow-energy-width projections. The new algorithm improves the accuracy of obtaining narrow-energy-width projections.

High-dynamic-range X-ray CT imaging method based on energy self-adaptation between scanning angles

High-dynamic-range (HDR) X-ray CT imaging is effective in detecting some complex structures. For previous low-dynamic-range (LDR) imaging detectors, multi-energy LDR image sequence fusion can extend the dynamic range, but the efficiency is decreased. However, with the application of HDR imaging devices, traditional fixed-energy X-ray imaging can cause incongruity within energy, dynamic range, and the equivalent thickness of the workpiece at different projection angles. Then, the projection has a blurred edge, and the CT image quality is poor because of scattering and the inadequate dose. In this paper, a new HDR X-ray CT imaging method with energy self-adaptation between scanning angles for HDR imaging devices is studied. Low-energy prescanning is used to determine the initial scanning energy and obtain the edge contour information with an attenuating effect on scattering. By establishing a mathematical model between the gray level of the projection and the transmission voltage, the transmission energy at each angle is adjusted adaptively. Then, the prescanning and energy self-adaption scanning projections are fused to obtain the complete projection of the complex workpiece. Finally, a conventional reconstruction algorithm is used to reconstruct the HDR CT image. The experimental results show that the proposed imaging method can achieve HDR CT imaging of complex structures with high reconstruction quality, clear edge details, and high completeness.

High dynamic range fluorescence imaging

Fluorescence acquisition and image display over a high dynamic range is highly desirable. However, the limited dynamic range of current photodetectors and imaging CCDs impose a limit on the fluorescence intensities that can be simultaneously captured during a single image acquisition. This is particularly troublesome when imaging biological samples, where protein expression fluctuates considerably. As a result, biological images will often contain regions with signal that is either saturated or hidden within background noise, causing information loss. In this manuscript we summarize recent work from our group and others, to extended conventional to high dynamic range fluorescence imaging. These strategies have many biological applications, such as mapping of neural connections, vascular imaging, bio-distribution studies or pharmacologic imaging at the single cell and organ level.

Consecutive Short-Scan CT for Geological Structure Analog Models with Large Size on In-Situ Stage

For the analysis of interior geometry and property changes of a large-sized analog model during a loading or other medium (water or oil) injection process with a non-destructive way, a consecutive X-ray computed tomography (XCT) short-scan method is developed to realize an in-situ tomography imaging. With this method, the X-ray tube and detector rotate 270° around the center of the guide rail synchronously by switching positive and negative directions alternately on the way of translation until all the needed cross-sectional slices are obtained. Compared with traditional industrial XCTs, this method well solves the winding problems of high voltage cables and oil cooling service pipes during the course of rotation, also promotes the convenience of the installation of high voltage generator and cooling system. Furthermore, hardware costs are also significantly decreased. This kind of scanner has higher spatial resolution and penetrating ability than medical XCTs. To obtain an effective sinogram which matches rotation angles accurately, a structural similarity based method is applied to elimination of invalid projection data which do not contribute to the image reconstruction. Finally, on the basis of geometrical symmetry property of fan-beam CT scanning, a whole sinogram filling a full 360° range is produced and a standard filtered back-projection (FBP) algorithm is performed to reconstruct artifacts-free images.