Sparse-view neutron CT 3D image reconstruction algorithm based on split Bregman method

As a complement to X-ray computed tomography(CT),neutron tomography has been extensively used in nuclear engineer-ing,materials science,cultural heritage,and industrial applications.Reconstruction of the attenuation matrix for neutron tomography with a traditional analytical algorithm requires hundreds of projection views in the range of 0°to 180°and typically takes several hours to complete.Such a low time-resolved resolution degrades the quality of neutron imaging.Decreasing the number of projection acquisitions is an important approach to improve the time resolution of images;however,this requires efficient reconstruction algorithms.Therefore,sparse-view reconstruction algorithms in neutron tomography need to be investigated.In this study,we investigated the three-dimensional reconstruction algorithm for sparse-view neu-tron CT scans.To enhance the reconstructed image quality of neutron CT,we propose an algorithm that uses OS-SART to reconstruct images and a split Bregman to solve for the total variation(SBTV).A comparative analysis of the performances of each reconstruction algorithm was performed using simulated and actual experimental data.According to the analyzed results,OS-SART-SBTV is superior to the other algorithms in terms of denoising,suppressing artifacts,and preserving detailed structural information of images.

Image Reconstruction from Fan-Beam Projections without Back-Projection Weight in a 2-D Dynamic CT: Compensation of Time-Dependent Rotational, Uniform Scaling and Translational Deformations

In a dynamic CT, the acquired projections are corrupted due to strong dynamic nature of the object, for example: lungs, heart etc. In this paper, we present fan-beam reconstruction algorithm without position-dependent backprojection weight which compensates for the time-dependent translational, uniform scaling and rotational deformations occurring in the object of interest during the data acquisition process. We shall also compare the computational cost of the proposed reconstruction algorithm with the existing one which has position-dependent weight. To accomplish the objective listed above, we first formulate admissibility conditions on deformations that is required to exactly reconstruct the object from acquired sequential deformed projections and then derive the reconstruction algorithm to compensate the above listed deformations satisfying the admissibility conditions. For this, 2-D time-dependent deformation model is incorporated in the fan-beam FBP reconstruction algorithm with no backprojection weight, assuming the motion parameters being known. Finally the proposed reconstruction algorithm is evaluated with the motion corrupted projection data simulated on the computer.

Research on CT characteristics reconstruction technology

The traditional computed tomography(CT)reconstruction methods are noisy,low resolution,poor contrast,and generally not suitable to detect the smaller flaws.Besides,the filter design is also difficult.The CT characteristics reconstruction technology was brought forward to improve in these aspects,which is defined to directly reconstruct the characteristics of the projection for the best requirements not the overall image quality.The two-dimension(2D)and three-dimension(3D)CT characteristics reconstruction algorithm were firstly introduced,then by detailed analysis,experimental results and comparsion of parameters calculated,its advantages in keeping better high-frequency feature,better noise immunity,short time-consuming and easier design are verified.

Investigation of prior image constrained compressed sensing-based spectral X-ray CT image reconstruction

To improve spectral X-ray CT reconstructed image quality, the energy-weighted reconstructed image xbins^W and the separable paraboloidal surrogates（SPS） algorithm are proposed for the prior image constrained compressed sensing（PICCS）-based spectral X-ray CT image reconstruction. The PICCS-based image reconstruction takes advantage of the compressed sensing theory, a prior image and an optimization algorithm to improve the image quality of CT reconstructions.To evaluate the performance of the proposed method, three optimization algorithms and three prior images are employed and compared in terms of reconstruction accuracy and noise characteristics of the reconstructed images in each energy bin.The experimental simulation results show that the image xbins^W is the best as the prior image in general with respect to the three optimization algorithms; and the SPS algorithm offers the best performance for the simulated phantom with respect to the three prior images. Compared with filtered back-projection（FBP）, the PICCS via the SPS algorithm and xbins^W as the prior image can offer the noise reduction in the reconstructed images up to 80. 46%, 82. 51%, 88. 08% in each energy bin,respectively. M eanwhile, the root-mean-squared error in each energy bin is decreased by 15. 02%, 18. 15%, 34. 11% and the correlation coefficient is increased by 9. 98%, 11. 38%,15. 94%, respectively.

Image reconstruction based on total-variation minimization and alternating direction method in linear scan computed tomography

Linear scan computed tomography （LCT） is of great benefit to online industrial scanning and security inspection due to its characteristics of straight-line source trajectory and high scanning speed. However, in practical applications of LCT, there are challenges to image reconstruction due to limited-angle and insufficient data. In this paper, a new reconstruction algorithm based on total-variation （TV） minimization is developed to reconstruct images from limited-angle and insufficient data in LCT. The main idea of our approach is to reformulate a TV problem as a linear equality constrained problem where the objective function is separable, and then minimize its augmented Lagrangian function by using alternating direction method （ADM） to solve subproblems. The proposed method is robust and efficient in the task of reconstruction by showing the convergence of ADM. The numerical simulations and real data reconstructions show that the proposed reconstruction method brings reasonable performance and outperforms some previous ones when applied to an LCT imaging problem.

Gray weighted algorithm for variable voltage CT reconstruction

In conventional computed tomography （CT） reconstruction based on fixed voltage, the projective data often ap- pear overexposed or underexposed, as a result, the reconstructive results are poor. To solve this problem, variable voltage CT reconstruction has been proposed. The effective projective sequences of a structural component are obtained through the variable voltage. The total variation is adjusted and minimized to optimize the reconstructive results on the basis of iterative image using algebraic reconstruction technique （ART）. In the process of reconstruction, the reconstructive image of low voltage is used as an initial value of the effective proiective reconstruction of the adjacent high voltage, and so on until to the highest voltage according to the gray weighted algorithm. Thereby the complete structural information is reconstructed. Simulation results show that the proposed algorithm can completely reflect the information of a complicated structural com- ponent, and the pixel values are more stable than those of the conventional.

High-Quality Three-Dimensional Computed Tomography Angiography of Abdominal Viscera with Small Focal Spot, Low Tube Voltage, and Iterative Model Reconstruction Technique

Purpose: To evaluate the quality of three-dimensional (3D) CT angiography images of the abdominal viscera with small focal spot, low tube voltage, and iterative model reconstruction technique (IMR). Materials and Methods: Seven patients with suspected disease of the pancreatobiliary system had undergone CT with high-quality CTA protocol in the present study. There were 5 men and 2 women, ranging in age from 52 to 80 years (mean: 64 years). Results: Depiction of abdominal small artery, small portal vein was possible in all cases. In two cases that we were able to compare, it was superior to standard CTA in small vascular depiction in CTA made clearly in high quality protocol. Conclusions: Although the use of small focal spot, low tube voltage, and IMR can produce higher-quality images of abdominal vessels than standard CTA, this improvement is not significant at elevated radiation doses.

Hybrid reconstruction algorithm for computed tomography based on diagonal total variation

Inspired by total variation(TV), this paper represents a new iterative algorithm based on diagonal total variation(DTV) to address the computed tomography image reconstruction problem. To improve the quality of a reconstructed image, we used DTV to sparsely represent images when iterative convergence of the reconstructed algorithm with TV-constraint had no effect during the reconstruction process. To investigate our proposed algorithm, the numerical and experimental studies were performed, and rootmean-square error(RMSE) and structure similarity(SSIM)were used to evaluate the reconstructed image quality. The results demonstrated that the proposed method could effectively reduce noise, suppress artifacts, and reconstruct highquality image from incomplete projection data.

Reduction of artifacts in dental cone beam CT images to improve the three dimensional image reconstruction

Cone-beam CT (CBCT) scanners are based on volumetric tomography, using a 2D extended digital array providing an area detector [1,2]. Compared to traditional CT, CBCT has many advantages, such as less X-ray beam limitation, and rapid scan time, etc. However, in CBCT images the x-ray beam has lower mean kilovolt (peak) energy, so the metal artifact is more pronounced on. The position of the shadowed region in other views can be tracked by projecting the 3D coordinates of the object. Automatic image segmentation was used to replace the pixels inside the metal object with the boundary pixels. The modified projection data, using synthetically Radon Transformation, were then used to reconstruct a new back projected CBCT image. In this paper, we present a method, based on the morphological, area and pixel operators, which we applied on the Radon transformed image, to reduce the metal artifacts in CBCT, then we built the Radon back project images using the radon invers transformation. The artifacts effects on the 3d-reconstruction is that, the soft tissues appears as bones or teeth. For the preprocessing of the CBCT images, two methods are used to recognize the noisy black areas that the first depends on thresholding and closing algorithm, and the second depends on tracing boundaries after using thresholding algorithm too. The intensity of these areas is the lowest in the image than other tissues, so we profit this property to detect the edges of these areas. These two methods are applied on phantom and patient image data. It deals with reconstructed CBCT dicom images and can effectively reduce such metal artifacts. Due to the data of the constructed images are corrupted by these metal artifacts, qualitative and quantitative analysis of CBCT images is very essential.

3D reconstruction method and connectivity rules of fracture networks generated under different mining layouts

In current research, a series of triaxial tests, which were employed to simulate three typical mining lay-outs (i.e., top-coal caving, non-pillar mining and protected coal seam mining), were conducted on coal by using MTS815 Flex Test GT rock mechanics test system, and the fracture networks in the broken coal samples were qualitatively and quantitatively investigated by employing CT scanning and 3D reconstruc-tion techniques. This work aimed at providing a detail description on the micro-structure and fracture-connectivity characteristics of rupture coal samples under different mining layouts. The results show that: (i) for protected coal seam mining layout, the coal specimens failure is in a compression-shear manner and oppositely, (ii) the tension-shear failure phenomenon is observed for top-coal caving and non-pillar mining layouts. By investigating the connectivity features of the generated fractures in the direction of r1 under different mining layouts, it is found that the connectivity level of the fractures of the samples corresponding to non-pillar mining layout was the highest.

Randomized Kaczmarz algorithm for CT reconstruction

The order of the projection in the algebraic reconstruction technique(ART)method has great influence on the rate of the convergence.Although many scholars have studied the order of the projection,few theoretical proofs are given.Thomas Strohmer and Roman Vershynin introduced a randomized version of the Kaczmarz method for consistent,and over-determined linear systems and proved whose rate does not depend on the number of equations in the systems in 2009.In this paper,we apply this method to computed tomography(CT)image reconstruction and compared images generated by the sequential Kaczmarz method and the randomized Kaczmarz method.Experiments demonstrates the feasibility of the randomized Kaczmarz algorithm in CT image reconstruction and its exponential curve convergence.

Failed medial patellofemoral ligament reconstruction:Causes and surgical strategies

Patel ar instability is a common clinical problem encountered by orthopedic surgeons specializing in the knee. For patients with chronic lateral patellar instability, the standard surgical approach is to stabilize the patella through a medial patellofemoral ligament(MPFL) reconstruction. Foreseeably, an increasing number of revision surgeries of the reconstructed MPFL will be seen in upcoming years. In this paper, the causes of failed MPFL reconstruction are analyzed:(1) incorrect surgical indication or inappropriate surgical technique/patient selection;(2) a technical error; and(3) an incorrect assessment of the concomitant risk factors for instability. An understanding of the anatomy and biomechanics of the MPFL and cautiousness with the imaging techniques while favoring clinical over radiological findings and the use of common sense to determine the adequate surgical technique for each particular case, are critical to minimizing MPFL surgery failure. Additionally, our approach to dealing with failure after primary MPFL reconstruction is also presented.

Design Consideration and Reconstruction Method for Double-source Double-multislice Spiral CT

To accelerate the scan speed and improve the image quality, a new type of CT configuration, "double-source double-multislice spiral CT" (DSDMS-CT), which is based on two sets of single-source multislice spiral CT was proposed with a special reconstruction algorithm. Simulation results using the fan-beam filtered backprojection algorithm with a special interpolation method were presented for both single-source multislice spiral CT and DSDMS-CT. The results of new CT model show that it scans faster than the traditional spiral CT and has a better slice sensitivity profile (SSP) with larger pitch value.

A practical image reconstruction and processing method for symmetrically off-center detector CBCT system

CBCT scanners have been widely used in angiography,radiotherapy guidance,mammography and oral maxillofacial imaging.To cut detector size,reduce manufacturing costs and radiation dose while keeping a reasonable FOV,the flat panel detector can be placed off-center horizontally.This scanning configuration extends the FOV effectively.However,each projection is transversely truncated,bringing errors and artifacts in reconstruction.In this paper,a simple but practical method is proposed for this scanning geometry based on truncation compensation and the modified FDK algorithm.Numerical simulations with jaw phantom were conducted to evaluate the accuracy and practicability of the proposed method.A novel CBCT system for maxillofacial imaging is used for clinical test,which is equipped with an off-center small size flat panel detector.Results show that reconstruction accuracy is acceptable for clinical use,and the image quality appears sufficient for specific diagnostic requirements.It provides a novel solution for clinical CBCT system,in order to reduce radiation dose and manufacturing cost.

Vertebrae CT Images 3D Reconstruction with Improve Marching Cubes Algorithm

Medical images 3D reconstruction is an important part in medical image analysis and processing. Although lots of algorithms have been proposed continuously, speed and accuracy cannot conform to actual needs, which has always been the focus topic. In this paper, we propose an Improved Marching Cubes algorithm ( I-MC) based on the surface rendering theory, which implements 3D reconstruction of the vertebrae. Firstly, we preprocessed the original 2D vertebrae CT images with the bilateral-filter denoising algorithm. Secondly, on the basis of the traditional Marching Cubes algorithm, the seed voxels were extracted and the Region Growing algorithm was used to determine all voxels that contain isosurfaces. Then, the Golden Section instead of the traditional linear interpolation was used to calculate the equivalent point, and this method reduced the calculations of public edges. VTK and OpenGL implemented 3D reconstruction of the vertebrae on GPU quickly and accurately. The experimental results show that when compared with the traditional Marching Cubes algorithm and Mesh Simplification Marching Cubes algorithm, the improved algorithm achieves a significant improvement of reconstruction speed while preserving the accurate results. The efficiency of algorithm is improved dramatically. This method is real-time and achieves the goal of efficient 3D reconstruction of vertebrae CT images.

PC-BASED SURFACE RECONSTRUCTION OF MEDICAL CT IMAGES

It is an active research area to reconstruct 3-D object and display its visible surfacesfrom cross-sectional images. In this paper, the methods of reconstructing 3-D object from medicalCT images and displaying the visible surfaces are discussed. A polygon approximation methodthat forms polygon with the same number of segment points and a fast interpolation method forcross-sectional contours are presented at first. Then the voxel set of a human liver is reconstructed.And then the liver voxel set is displayed using depth and gradient shading methods. The softwareis written in C programming language at a microcomputer image processing system with a PC/ATcomputer as the host and a PC-VISION board as the image processing unit. The result of theprocessing is satisfying.

Evaluation of the Optimal Image Reconstruction Interval for Noninvasive Coronary 64-Slice Computed Tomography Venography

Objective: We investigated the appropriate reconstruction interval required to generate optimal quality images of the coronary veins and to evaluate the size of each vein at the systolic and diastolic phases using coronary computed tomography (CT) venography. Methods: Coronary CT venograms obtained from 30 patients using 64-slice CT were reconstructed at 0% to 90% of the cardiac cycle in 10% increments. Two radiologists assessed the image quality of the anterior interventricular vein (AIV), the great cardiac vein (GCV), the posterior vein of the left ventricle (PVLV), the posterior interventricular vein (PIV), the coronary sinus (CS) and the small cardiac vein (SCV). We determined the sizes of measurable CS (n = 16) and GCV (n = 12) at the end systolic and mid diastolic phases. Results: The most appropriate reconstruction point for all coronary veins turned out to be at the mid-diastolic phase. The size of the CS and GCV was greater at a 30% than that at a 70% R-R interval (p Conclusions: Image quality was optimal at the mid-diastolic phase for each coronary vein, but the sizes of the coronary veins varied during the cardiac cycle. The cardiac cycle must be considered when measuring the sizes of cardiac veins.

Significance of an Advanced Image-Based Virtual Monoenergetic Reconstruction of Dual Source Dual-Energy CT Data at Low keV Increases Image Quality for Portal Vein System of Pancreatic Cancer Patients

Purpose: To explore the significance of dual-source computed tomography (DECT) virtual monoenergetic reconstructions technology in improving image quality for portal vein system of pancreatic cancer patients. Materials and methods: 47 patients with clinically suspected pancreatic cancer (all confirmed by pathology) were collected. Routine plain scan was performed with Siemens Force dual-source dual-energy CT followed by 3 scans respectively carried out in arterial phase, portal phase and delayed phase. Traditional virtual monoenergetic reconstructions (Mono_E) and new generation of virtual monoenergetic reconstructions (Mono+) were respectively performed on portal vein images to obtain virtual single energy images including Mono_ E70 keV, Mono_E 55 keV and Mono+ 70 keV and Mono+ 55 keV. The signal-to-noise ratio (SNR) and noise of portal vein, normal pancreatic tissues and pancreatic lesions of 100 kV, Mono_E and Mono+ images were compared. In addition, the contrast noise ratio of portal vein and lesions as well as pancreatic tissues and lesions (CNR PV, CNRtumor) were also compared. At the same time, two imaging physicians with rich clinical experiences read the films and scored the images of each group by using the 5-point scoring method. Results: Mono+ 55 keV images including SNRpv, SNRpanc, SNRtumor, Noise, CNRpv, CNRtumor were statistically different from 100 KV images and Mono_E images (P < 0.05). As for the subjective score, Mono+ 55 keV image score also had the highest score, which had statistical significance (P < 0.05). The results showed that Mono+ 55 keV images had the best quality. Conclusion: The new generation of virtual Mono+ post-treatment can reduce image noise. Low energy Mono+ images can improve the contrast between pancreatic cancer lesions and portal of pancreatic cancer patients.

Derivative-Hilbert-Backprojection based image reconstruction from truncated projections in helical cone-beam CT

In helical cone-beam computed tomography(CT), Feldkamp-Davis-Kress(FDK) based image reconstruction algorithms are by far the most popular. However, artifacts are commonly met in the presence of lateral projection truncation. The reason is that the ramp filter is global. To restrain the truncation artifacts, an approximate reconstruction formula is proposed based on the Derivative-Hilbert-Backprojection(DHB) framework. In the method, the first order derivative filter is followed by the Hilbert transform. Since the filtered projection values are almost zero by the first order derivative filter, the following Hilbert transform has little influence on the projection values, even though the projections are laterally truncated. The proposed method has two main advantages. First, it has comparable computational efficiency and image quality as well as the conventional helical FDK algorithm for non-truncated projections. The second advantage is that images can be reconstructed with acceptable quality and much lower computational cost in comparison to the Laplace operator based algorithm in cases with truncated projections. To point out the advantages of our method, simulations on the computer and real data experiments on our laboratory industrial cone-beam CT are conducted. The simulated and experimental results demonstrate that the method is feasible for image reconstruction in the case of projection truncation.

Compressed sensing and Otsu's method based binary CT image reconstruction technique in non-destructive detection

This paper tries to address the problem of binary CT image reconstruction in non-destructive detection with an algorithm based on compressed sensing(CS) and Otsu's method, which could reconstruct binary CT image of test object from incomplete detection data. According to binary CT image characteristics, we employ Splitbregman method based on L1/2regularization to solve piecewise constant region reconstruction. To improve the reconstructed image quality from incomplete detection data, we utilize a priori knowledge and Otsu's method as the optimization constraint. In our study, we make numerical simulation to investigate our proposed method,and compare reconstructed results from different reconstruction methods. Finally, the experimental results demonstrate that the proposed method could effectively reduce noise and suppress artifacts, and reconstruct high-quality binary image from incomplete detection data.