There is a contradiction between the evolution rate of materials and the time resolution of SR-CT characterization in the in situ synchrotron radiation computed tomography(SR-CT)characterization of ultrafast evolution...There is a contradiction between the evolution rate of materials and the time resolution of SR-CT characterization in the in situ synchrotron radiation computed tomography(SR-CT)characterization of ultrafast evolution process.The sampling strategy of the ultra-sparse angle is an effective method for improving time resolution.Accurate reconstruction under sparse sampling conditions has always been a bottleneck problem.In recent years,convolutional neural networks have shown outstanding advantages in sparse-angle CT reconstruction given the development of deep learning.However,existing ideas did not consider the expression of high-frequency details in neural networks,limiting their application in accurate SR-CT characterization.A novel high-frequency information-constrained deep learning network(HFIC-Net)is proposed in response to this problem.Additional high-frequency information constraints are added to improve the accuracy of the reconstruction results.Further,a series of numerical reconstruction experiments are conducted to verify this new method,and the results indicate that the reconstruction results of HFIC-Net method effectively improve reconstruction quality.This new method uses only eight-angle projections to achieve the reconstruction effect of the filtered backprojection method(FBP)method in 360 projections.The results of the HFIC-Net method demonstrate clear boundaries and accurate detailed structures,correcting the misinformation caused by using other methods.For quantitative evaluation,the SSIM used to evaluate image structure similarity is increased from 0.1951,0.9212,and 0.9308 for FBP,FBP-Conv,and DDC-Net,respectively,to 0.9620 for HFIC-Net.Finally,the results of actual SR-CT experimental data indicate that the new method can suppress artifacts and achieve accurate reconstruction,and it is suitable for the in situ SR-CT accurate characterization of ultxafast evolution process.展开更多
Rotational computed laminography(CL)has broad application potential in three-dimensional imaging of plate-like objects because it only requires X-rays to pass through the tested object in the thickness direction durin...Rotational computed laminography(CL)has broad application potential in three-dimensional imaging of plate-like objects because it only requires X-rays to pass through the tested object in the thickness direction during the imaging process.In this study,a rectangular cross-section field-of-view rotational CL(RC-CL)is proposed for circuit board imaging.Compared to other rotational CL systems,the field of view is the largest and most suitable for rectangular circuit boards.Meanwhile,as the imaging geometry of RC-CL is significantly different from that of cone-beam CT,the Feldkamp-Davis-Kress(FDK)reconstruction algorithm cannot be used directly.However,transferring the projection data to fit into the CBCT geometry using two-dimensional interpolation introduces interpolation errors.Therefore,an FDK-type analytical reconstruction algorithm applicable to RC-CL was developed.The effectiveness of the method was validated through numerical experiments,and the influence of the tilt angle on the reconstruction results was analyzed.Finally,the RC-CL technique was applied to real defect detection research on circuit boards.展开更多
Grating-based X-ray phase-contrast imaging enhances the contrast of imaged objects,particularly soft tissues.However,the radiation dose in computed tomography(CT)is generally excessive owing to the complex collection ...Grating-based X-ray phase-contrast imaging enhances the contrast of imaged objects,particularly soft tissues.However,the radiation dose in computed tomography(CT)is generally excessive owing to the complex collection scheme.Sparse-view CT collection reduces the radiation dose,but with reduced resolution and reconstructed artifacts particularly in analytical reconstruction methods.Recently,deep learning has been employed in sparse-view CT reconstruction and achieved stateof-the-art results.Nevertheless,its low generalization performance and requirement for abundant training datasets have hindered the practical application of deep learning in phase-contrast CT.In this study,a CT model was used to generate a substantial number of simulated training datasets,thereby circumventing the need for experimental datasets.By training a network with simulated training datasets,the proposed method achieves high generalization performance in attenuationbased CT and phase-contrast CT,despite the lack of sufficient experimental datasets.In experiments utilizing only half of the CT data,our proposed method obtained an image quality comparable to that of the filtered back-projection algorithm with full-view projection.The proposed method simultaneously addresses two challenges in phase-contrast three-dimensional imaging,namely the lack of experimental datasets and the high exposure dose,through model-driven deep learning.This method significantly accelerates the practical application of phase-contrast CT.展开更多
Radiation dose reduction in computed tomography(CT)can be achieved by decreasing the number of projections.However,reconstructing CT images via filtered back projection algorithm from sparse-view projections often con...Radiation dose reduction in computed tomography(CT)can be achieved by decreasing the number of projections.However,reconstructing CT images via filtered back projection algorithm from sparse-view projections often contains severe streak artifacts,affecting clinical diagnosis.To address this issue,this paper proposes TransitNet,an iterative unrolling deep neural network that combines model-driven data consistency,a physical a prior constraint,with deep learning’s feature extraction capabilities.TransitNet employs a novel iterative architecture,implementing flexible physical constraints through learnable data consistency operations,utilizing Transformer’s self-attention mechanism to model long-range dependencies in image features,and introducing linear attention mechanisms to reduce self-attention’s computational complexity from quadratic to linear.Extensive experiments demonstrate that this method exhibits significant advantages in both reconstruction quality and computational efficiency,effectively suppressing streak artifacts while preserving structures and details of images.展开更多
Objective To compare the impact of different reconstruction algorithms on the image quality of 60 kVp head and neck CT angiography(CTA)using subjective and objective metrics,with a focus on vessel edge sharpness.Metho...Objective To compare the impact of different reconstruction algorithms on the image quality of 60 kVp head and neck CT angiography(CTA)using subjective and objective metrics,with a focus on vessel edge sharpness.Methods This prospective study enrolled 45 patients who underwent ultra-low-voltage(60 kVp)head and neck CTA.Image datasets were reconstructed with filtered back-projection(FBP),ClearView(CV)and ClearInfinity(CI)algorithms at low(30%),medium(50%),and high(70%)strengths.Image quality was assessed subjectively and objectively via the Kruskal‒Wallis test for multiple comparisons.Objective parameters,including edge rise slope(ERS)and edge rise distance(ERD),were analyzed via the Friedman test of multiple comparisons statistics.Results Subjective assessments favored the CI50 reconstruction algorithm,demonstrating superior or satisfactory results compared to the other algorithms,with significantly better vessel delineation,edge definition and diagnostic confidence(all P<0.05).Objective analysis revealed that the CV50 and CV70 algorithms significantly reduced ERS and/or elevated ERD(both P<0.05).However,the CI50 algorithm maintained comparable vessel edge sharpness(P>0.05)across all evaluated head and neck vascular segments when compared with the FBP algorithm.Conclusions The CI50 reconstruction algorithm optimizes image quality in 60 kVp head and neck CTA.It provides vessel edge sharpness comparable to FBP while offering superior vessel delineation,edge definition,and diagnostic confidence compared to FBP and CV algorithm.These findings suggest that CI50 has the potential to improve diagnostic accuracy in low-dose vascular imaging.展开更多
To better understand the biological structure of bigeye tuna(Thunnus obesus),albacore tuna(Thunnus alalunga),and longtail tuna(Thunnus tonggol),computed tomography(CT)was used to scan their bodies,and the data are pro...To better understand the biological structure of bigeye tuna(Thunnus obesus),albacore tuna(Thunnus alalunga),and longtail tuna(Thunnus tonggol),computed tomography(CT)was used to scan their bodies,and the data are processed by Mimics software.The skeleton,swim bladder,and muscle of the three tuna species are reconstructed in three dimensions.The surface area and volume of the corresponding parts are measured.The results show that the surface areas of the skeleton of longtail tuna,bigeye tuna,albacore tuna accounted for 28.18%,37.34%,33.45%of their whole body surface areas respectively;the surface areas of swim bladder accounted for 0,2.06%,2.72% of their whole body surface area respectively;and the surface areas of muscle accounted for 71.82%,60.6%,63.83%of their whole body surface areas respectively.And the volumes of skeleton accounted for 28.18%,8.05%,3.84%,the volumes of swim bladder accounted for 0,3.44%,0.92%,and the volumes of muscle accounted for 94.84%,88.51%,95.24%of their body volumes respectively.The swim bladder of the longtail tuna has degenerated,while that of the bigeye tuna is conical,exhibiting the highest volume proportion among the three species.In contrast,the swim bladder of the albacore tuna is both flat and elongated,resembling an arc.Additionally,the surface area and the volume of the bigeye tuna’s swim bladder differ signifi-cantly from those of the albacore tuna.Regarding skeletal and muscular structures,the bigeye tuna has the highest skeletal volume proportion(8.05%),whereas the albacore tuna exhibits the highest muscle volume proportion(95.24%).These morphological differences are closely associated with their respective habitats.This study demonstrates the potential of CT technology in fish morphological research,providing a reliable,non-invasive method for analyzing internal structures,quantifying organ characteristics and improving the accuracy of acoustic stock assessment.展开更多
Globally,liver cancer ranks as the sixth most frequent malignancy cancer.The importance of early detection is undeniable,as liver cancer is the fifth most common disease in men and the ninth most common cancer in wome...Globally,liver cancer ranks as the sixth most frequent malignancy cancer.The importance of early detection is undeniable,as liver cancer is the fifth most common disease in men and the ninth most common cancer in women.Recent advances in imaging,biomarker discovery,and genetic profiling have greatly enhanced the ability to diagnose liver cancer.Early identification is vital since liver cancer is often asymptomatic,making diagnosis difficult.Imaging techniques such as Magnetic Resonance Imaging(MRI),Computed Tomography(CT),and ultrasonography can be used to identify liver cancer once a sample of liver tissue is taken.In recent research,reliable detection of liver cancer with minimal computing computational complexity and time has remained a serious difficulty.This paper employs the DenseNet model to enhance the detection of liver nodules with tumors by segmenting them using UNet and VGG using Fastai(UVF)in CT images.Its dense interconnections distinguish the DenseNet between layers.These dense connections facilitate the propagation of gradients and the flow of information throughout the network,thereby enhancing the efficacy and performance of training.DenseNet’s architecture combines dense blocks,bottleneck layers,and transition layers,allowing it to achieve a compromise between expressiveness and computing efficiency.Finally,the 3D liver nodular models were created using a raycasting volume rendering approach.Compared to other state-of-the-art deep neural networks,it is suitable for clinical applications to assist doctors in diagnosing liver cancer.The proposed approach was tested on a 3Dircadb dataset.According to experiments,UVF segmentation on the 3Dircadb dataset is 97.9%accurate.According to the study,the DenseNet and UVF segment liver cancer better than prior methods.The system proposes automated 3D liver cancer tumor visualization.展开更多
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 m...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.展开更多
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 characteri...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.展开更多
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 compres...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.展开更多
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 prac...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.展开更多
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 reco...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.展开更多
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...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.展开更多
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 Meth...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.展开更多
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 limita...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.展开更多
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...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.展开更多
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 proof...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.展开更多
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...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.展开更多
基金supported by the National Nature Science Foundation of China(Nos.12027901 and 12041202)Synchrotron Radiation Joint Fund of University of Science and Technology of China(Nos.KY2090000059 and KY2090000054)。
文摘There is a contradiction between the evolution rate of materials and the time resolution of SR-CT characterization in the in situ synchrotron radiation computed tomography(SR-CT)characterization of ultrafast evolution process.The sampling strategy of the ultra-sparse angle is an effective method for improving time resolution.Accurate reconstruction under sparse sampling conditions has always been a bottleneck problem.In recent years,convolutional neural networks have shown outstanding advantages in sparse-angle CT reconstruction given the development of deep learning.However,existing ideas did not consider the expression of high-frequency details in neural networks,limiting their application in accurate SR-CT characterization.A novel high-frequency information-constrained deep learning network(HFIC-Net)is proposed in response to this problem.Additional high-frequency information constraints are added to improve the accuracy of the reconstruction results.Further,a series of numerical reconstruction experiments are conducted to verify this new method,and the results indicate that the reconstruction results of HFIC-Net method effectively improve reconstruction quality.This new method uses only eight-angle projections to achieve the reconstruction effect of the filtered backprojection method(FBP)method in 360 projections.The results of the HFIC-Net method demonstrate clear boundaries and accurate detailed structures,correcting the misinformation caused by using other methods.For quantitative evaluation,the SSIM used to evaluate image structure similarity is increased from 0.1951,0.9212,and 0.9308 for FBP,FBP-Conv,and DDC-Net,respectively,to 0.9620 for HFIC-Net.Finally,the results of actual SR-CT experimental data indicate that the new method can suppress artifacts and achieve accurate reconstruction,and it is suitable for the in situ SR-CT accurate characterization of ultxafast evolution process.
基金supported by the National Key Research and Development Program of China(No.2022YFF0607802)。
文摘Rotational computed laminography(CL)has broad application potential in three-dimensional imaging of plate-like objects because it only requires X-rays to pass through the tested object in the thickness direction during the imaging process.In this study,a rectangular cross-section field-of-view rotational CL(RC-CL)is proposed for circuit board imaging.Compared to other rotational CL systems,the field of view is the largest and most suitable for rectangular circuit boards.Meanwhile,as the imaging geometry of RC-CL is significantly different from that of cone-beam CT,the Feldkamp-Davis-Kress(FDK)reconstruction algorithm cannot be used directly.However,transferring the projection data to fit into the CBCT geometry using two-dimensional interpolation introduces interpolation errors.Therefore,an FDK-type analytical reconstruction algorithm applicable to RC-CL was developed.The effectiveness of the method was validated through numerical experiments,and the influence of the tilt angle on the reconstruction results was analyzed.Finally,the RC-CL technique was applied to real defect detection research on circuit boards.
基金supported by the National Natural Science Foundation of China(Nos.U2032148,U2032157,11775224)USTC Research Funds of the Double First-Class Initiative(No.YD2310002008)the National Key Research and Development Program of China(No.2017YFA0402904),the Youth Innovation Promotion Association,CAS(No.2020457)。
文摘Grating-based X-ray phase-contrast imaging enhances the contrast of imaged objects,particularly soft tissues.However,the radiation dose in computed tomography(CT)is generally excessive owing to the complex collection scheme.Sparse-view CT collection reduces the radiation dose,but with reduced resolution and reconstructed artifacts particularly in analytical reconstruction methods.Recently,deep learning has been employed in sparse-view CT reconstruction and achieved stateof-the-art results.Nevertheless,its low generalization performance and requirement for abundant training datasets have hindered the practical application of deep learning in phase-contrast CT.In this study,a CT model was used to generate a substantial number of simulated training datasets,thereby circumventing the need for experimental datasets.By training a network with simulated training datasets,the proposed method achieves high generalization performance in attenuationbased CT and phase-contrast CT,despite the lack of sufficient experimental datasets.In experiments utilizing only half of the CT data,our proposed method obtained an image quality comparable to that of the filtered back-projection algorithm with full-view projection.The proposed method simultaneously addresses two challenges in phase-contrast three-dimensional imaging,namely the lack of experimental datasets and the high exposure dose,through model-driven deep learning.This method significantly accelerates the practical application of phase-contrast CT.
基金National Natural Science Foundation of China under grant (62071281)Local Science and Technology Development Fund Project Guided by the Central Government under grant (YDZJSX2021A003)。
文摘Radiation dose reduction in computed tomography(CT)can be achieved by decreasing the number of projections.However,reconstructing CT images via filtered back projection algorithm from sparse-view projections often contains severe streak artifacts,affecting clinical diagnosis.To address this issue,this paper proposes TransitNet,an iterative unrolling deep neural network that combines model-driven data consistency,a physical a prior constraint,with deep learning’s feature extraction capabilities.TransitNet employs a novel iterative architecture,implementing flexible physical constraints through learnable data consistency operations,utilizing Transformer’s self-attention mechanism to model long-range dependencies in image features,and introducing linear attention mechanisms to reduce self-attention’s computational complexity from quadratic to linear.Extensive experiments demonstrate that this method exhibits significant advantages in both reconstruction quality and computational efficiency,effectively suppressing streak artifacts while preserving structures and details of images.
基金the Grant from the National Key Research and Development Program of China(No.2024YFC2419300)the National Natural Science Foundation of China(No.82471967)+1 种基金the Hubei Provincial Key Research and Development Program(No.2024BCB008)the Hubei Provincial Natural Science Foundation of China(No.2025AFB733).
文摘Objective To compare the impact of different reconstruction algorithms on the image quality of 60 kVp head and neck CT angiography(CTA)using subjective and objective metrics,with a focus on vessel edge sharpness.Methods This prospective study enrolled 45 patients who underwent ultra-low-voltage(60 kVp)head and neck CTA.Image datasets were reconstructed with filtered back-projection(FBP),ClearView(CV)and ClearInfinity(CI)algorithms at low(30%),medium(50%),and high(70%)strengths.Image quality was assessed subjectively and objectively via the Kruskal‒Wallis test for multiple comparisons.Objective parameters,including edge rise slope(ERS)and edge rise distance(ERD),were analyzed via the Friedman test of multiple comparisons statistics.Results Subjective assessments favored the CI50 reconstruction algorithm,demonstrating superior or satisfactory results compared to the other algorithms,with significantly better vessel delineation,edge definition and diagnostic confidence(all P<0.05).Objective analysis revealed that the CV50 and CV70 algorithms significantly reduced ERS and/or elevated ERD(both P<0.05).However,the CI50 algorithm maintained comparable vessel edge sharpness(P>0.05)across all evaluated head and neck vascular segments when compared with the FBP algorithm.Conclusions The CI50 reconstruction algorithm optimizes image quality in 60 kVp head and neck CTA.It provides vessel edge sharpness comparable to FBP while offering superior vessel delineation,edge definition,and diagnostic confidence compared to FBP and CV algorithm.These findings suggest that CI50 has the potential to improve diagnostic accuracy in low-dose vascular imaging.
基金funded by the National Key R&D Pro-gram(No.2023YFD2401301)the R&D Program of CNFC Overseas Fishery Co.,Ltd.(No.COFC-C-F-2024-004).
文摘To better understand the biological structure of bigeye tuna(Thunnus obesus),albacore tuna(Thunnus alalunga),and longtail tuna(Thunnus tonggol),computed tomography(CT)was used to scan their bodies,and the data are processed by Mimics software.The skeleton,swim bladder,and muscle of the three tuna species are reconstructed in three dimensions.The surface area and volume of the corresponding parts are measured.The results show that the surface areas of the skeleton of longtail tuna,bigeye tuna,albacore tuna accounted for 28.18%,37.34%,33.45%of their whole body surface areas respectively;the surface areas of swim bladder accounted for 0,2.06%,2.72% of their whole body surface area respectively;and the surface areas of muscle accounted for 71.82%,60.6%,63.83%of their whole body surface areas respectively.And the volumes of skeleton accounted for 28.18%,8.05%,3.84%,the volumes of swim bladder accounted for 0,3.44%,0.92%,and the volumes of muscle accounted for 94.84%,88.51%,95.24%of their body volumes respectively.The swim bladder of the longtail tuna has degenerated,while that of the bigeye tuna is conical,exhibiting the highest volume proportion among the three species.In contrast,the swim bladder of the albacore tuna is both flat and elongated,resembling an arc.Additionally,the surface area and the volume of the bigeye tuna’s swim bladder differ signifi-cantly from those of the albacore tuna.Regarding skeletal and muscular structures,the bigeye tuna has the highest skeletal volume proportion(8.05%),whereas the albacore tuna exhibits the highest muscle volume proportion(95.24%).These morphological differences are closely associated with their respective habitats.This study demonstrates the potential of CT technology in fish morphological research,providing a reliable,non-invasive method for analyzing internal structures,quantifying organ characteristics and improving the accuracy of acoustic stock assessment.
文摘Globally,liver cancer ranks as the sixth most frequent malignancy cancer.The importance of early detection is undeniable,as liver cancer is the fifth most common disease in men and the ninth most common cancer in women.Recent advances in imaging,biomarker discovery,and genetic profiling have greatly enhanced the ability to diagnose liver cancer.Early identification is vital since liver cancer is often asymptomatic,making diagnosis difficult.Imaging techniques such as Magnetic Resonance Imaging(MRI),Computed Tomography(CT),and ultrasonography can be used to identify liver cancer once a sample of liver tissue is taken.In recent research,reliable detection of liver cancer with minimal computing computational complexity and time has remained a serious difficulty.This paper employs the DenseNet model to enhance the detection of liver nodules with tumors by segmenting them using UNet and VGG using Fastai(UVF)in CT images.Its dense interconnections distinguish the DenseNet between layers.These dense connections facilitate the propagation of gradients and the flow of information throughout the network,thereby enhancing the efficacy and performance of training.DenseNet’s architecture combines dense blocks,bottleneck layers,and transition layers,allowing it to achieve a compromise between expressiveness and computing efficiency.Finally,the 3D liver nodular models were created using a raycasting volume rendering approach.Compared to other state-of-the-art deep neural networks,it is suitable for clinical applications to assist doctors in diagnosing liver cancer.The proposed approach was tested on a 3Dircadb dataset.According to experiments,UVF segmentation on the 3Dircadb dataset is 97.9%accurate.According to the study,the DenseNet and UVF segment liver cancer better than prior methods.The system proposes automated 3D liver cancer tumor visualization.
基金supported by the National Key Research and Development Program of China(No.2022YFB1902700)the National Natural Science Foundation of China(No.11875129)+3 种基金the Fund of the State Key Laboratory of Intense Pulsed Radiation Simulation and Effect(No.SKLIPR1810)the Fund of Innovation Center of Radiation Application(No.KFZC2020020402)the Fund of the State Key Laboratory of Nuclear Physics and Technology,Peking University(No.NPT2020KFY08)the Joint Innovation Fund of China National Uranium Co.,Ltd.,State Key Laboratory of Nuclear Resources and Environment,East China University of Technology(No.2022NRE-LH-02).
文摘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.
基金National Natural Science Foundation of China(No.61471325)
文摘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.
基金The National Natural Science Foundation of China(No.51575256)the Fundamental Research Funds for the Central Universities(No.NP2015101,XZA16003)the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)
文摘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.
基金the National High Technology Research and Development Program of China(Grant No.2012AA011603)
文摘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.
基金supported in part by the National Natural Science Foundation of China(No.61401049)the Chongqing Foundation and Frontier Research Project(Nos.cstc2016jcyjA0473,cstc2013jcyjA0763)+3 种基金the Graduate Scientific Research and Innovation Foundation of Chongqing,China(No.CYB16044)the Strategic Industry Key Generic Technology Innovation Project of Chongqing(No.cstc2015zdcy-ztzxX0002)China Scholarship Councilthe Fundamental Research Funds for the Central Universities Nos.CDJZR14125501,106112016CDJXY120003,10611CDJXZ238826
文摘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.
文摘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.
文摘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.
文摘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.
基金financially supported by the Major State Fundamental Research Project of China(Nos.2011CB201201and2010CB226802)the National Natural Science Foundation of China(No.51204113)the Youth Science and Technology Fund of Sichuan Province(No.2012JQ0031)
文摘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.
基金National Natural Science Foundation of China(No.61171179,No.61171178)Natural Science Foundation of Shanxi Province(No.2010011002-1,No.2010011002-2and No.2012021011-2)
文摘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.
文摘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.
