Image Reconstruction Algorithm
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Feng Chen ◽  
Deyun Chen ◽  
Lili Wang ◽  
Yang Botao

For the problems of low sensitivity, weak signal of high and low frequency and low signal-to-noise ratio in ECT, the mathematical model of the sensor is established. From the aspects of electrostatic field distribution and soft field effect, the influence of the structural parameters of the sensor on the sensor performance is analyzed. According to the influence of the components of the sensor on the sensitivity, the principle of optimal design is put forward. Based on the optimized Landweber image reconstruction algorithm, an ART image reconstruction algorithm with iterative correction is proposed, and the mathematical model of the algorithm is designed. According to constructing the target functional regularization term in the negative problems of electrical capacitance tomography, the iterative process of the modified art algorithm is deduced, and with adaptive step size, the convergence is speeded and accuracy of image reconstruction is improved. The experimental results show that the semi-convergence in the improved algorithm is obviously weakened, and the reconstructed image quality is better than that of the traditional art algorithm.

Shuyao Tian ◽  
Liancheng Zhang ◽  
Yajun Liu

It is difficult to control the balance between artifact suppression and detail preservation. In addition, the information contained in the reconstructed image is limited. For achieving the purpose of less lost information and lower computational complexity in the sampling process, this paper proposed a novel algorithm to realize the image reconstruction using sparse representation. Firstly, the principle of algorithm for sparse representation is introduced, and then the current commonly used reconstruction algorithms are described in detail. Finally, the algorithm can still process the image when the sparsity is unknown by introducing the sparsity theory and dynamically changing the step size to approximate the sparsity. The results explain that the improved algorithm can not only reconstruct the image with unknown sparsity, but also has advantages over other algorithms in reconstruction time. In addition, compared with other algorithms, the reconstruction time of the improved algorithm is the shortest under the same sampling rate.

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Xuliang Chen ◽  
Sichao Tai ◽  
Pengxiang Zhou ◽  
Xiao Chen

This study was to explore the application and effect of three-dimensional (3D) images of the esophagus in the treatment of atrial septal defect (ASD) combined with tricuspid regurgitation (TR) surgery under the processing of marching cubes (MC) image reconstruction algorithm. The MC image reconstruction algorithm was improved as the optimized MC image reconstruction algorithm. 100 patients who had successfully undergone the ASD combined with TR surgery in the hospital from January 2017 to December 2019 were selected as the research objects and grouped based on size of the defect. The preoperative and postoperative conditions of the patients were analyzed with the MC image reconstruction algorithm. Compared with the traditional MC image algorithm, the optimized MC was advanced with less running time and fewer fixed points ( P < 0.05 ). There were significant differences in TR of all ASD patients after the surgery ( P < 0.05 ), and the TR of all patients showed obvious declines from the 1st day to 30th day after surgery and gradually stabilized from the 3rd month to the 6th month after surgery. Compared with patients with normal pulmonary artery pressure, the amount of TR in patients with elevated pulmonary artery pressure increased significantly, and the difference was statistically significant ( P < 0.05 ). In addition, the improvement of TR after occlusion was correlated with the preoperative ASD of the patient. The optimized MC algorithm had been improved greatly in the number of fixed points and running time. The analysis using the optimized MC algorithm showed that ASD patients generally suffered different degrees of TR, TR increased with the increase of the defect, and good effect could be achieved in surgery of all kinds of ASD patients.

Ya-Ning Wang ◽  
Yu Du ◽  
Gao-Feng Shi ◽  
Qi Wang ◽  
Ru-Xun Li ◽  

OBJECTIVE: To investigate feasibility of applying deep learning image reconstruction (DLIR) algorithm in a low-kilovolt enhanced scan of the upper abdomen. METHODS: A total of 64 patients (BMI<28) are selected for the enhanced upper abdomen scan and divided evenly into two groups. The tube voltages in Group A are 100kV in arterial phase and 80kV in venous phase, while tube voltages are 120kV during two phases in Group B. Image reconstruction algorithms used in Group A include the filtered back projection (FBP) algorithm, the adaptive statistical iterative reconstruction-Veo (ASIR-V 40% and 80%) algorithm, and the DLIR algorithm (DL-L, DL-M, DL-H). Image reconstruction algorithm used in Group B is ASIR-V40%. The different reconstruction algorithm images are used to measure the common hepatic artery, liver, renal cortex, erector spinae, and subcutaneous adipose in the arterial phase and the average CT value and standard deviation of the portal vein, liver, spleen, erector spinae, and subcutaneous adipose in the portal phase. The signal-to-noise ratio (SNR) is calculated, and the images are also scored subjectively. RESULTS: In Group A, noise in the aorta, liver, portal vein (the portal phase), spleen (the portal phase), renal cortex, retroperitoneal adipose, and muscle is significantly lower in both the DL-H and ASIR-V80% images, and the SNR is significantly higher than those in the remaining groups (P<0.05). The SNR of each tissue and organ in Group B is not significantly different from that in DL-M, DL-L, and ASIR-V40% in Group A (P>0.05). The subjective image quality scores in the DL-H and B groups are higher than those in the other groups, and the FBP group has significantly lower image quality than the remaining groups (P<0.05). CONCLUSION: For upper abdominal low-kilovolt enhanced scan data, the DLIR-H gear yields a more satisfactory image quality than the FBP and ASIR-V.

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