Image Reconstruction Precision Research Articles

Radioactive source recognition with moving Compton camera imaging robot using Geant4

Robotics is becoming increasingly important in modern engineering areas. After the big nuclear accidents in Fukushima 2011, the crossing research of nuclear and robotics draws more and more attentions. In this paper, a method for radioactive source recognition using moving Compton camera imaging robot is proposed. In order to assess the quality of the reconstructed image, a new method called Cross-section Outline at Half Maximum (COHM) is proposed for three dimensional image reconstruction precision assessments. Two experiment validations using Geant4 platform are given which include the measurement with different distances and angles respectively. The result shows that the application of Compton camera imaging robot can improve the radioactive source image reconstruction quality. Based on the result of the experiment, several preconditions and suggestions are given to improve the image reconstruction precision when we apply robot to the radioactive source recognition. The research is focused on the three dimensional image reconstruction by using Compton camera imaging robot. It can improve the radioactive source recognition precision especially for three-dimensional contour recognition. And also it can supply good reference for the robot routine planning when we apply the robot into radioactive source recognition in future.

Investigation of Wavenumber Domain Imaging Algorithm for Ground-Based Arc Array SAR

Ground-based synthetic aperture radar (GB-SAR) has become an important technique for remote sensing deformation monitoring. However, most of the existing GB-SAR systems realize synthetic aperture by exploiting two closely spaced horn antennas to move along a linear rail. In order to obtain higher data acquisition efficiency and a wider view angle, we introduce arc antenna array technology into the GB-SAR system, which realizes a novel kind of system: ground-based arc array SAR (GB-AA-SAR). In this paper, we analyze arc observation geometry and derive analytic expressions of sampling criteria. Then, we propose a novel wavenumber domain imaging algorithm for GB-AA-SAR, which can achieve high image reconstruction precision through numerical solutions in the wavenumber domain. The proposed algorithm can be applied in wide azimuth view angle scenarios, and the problem of azimuth mismatch caused by distance approximation in arc geometric efficient omega-k imaging can be solved successfully. Finally, we analyze the two-dimensional (2D) spatial resolution of GB-AA-SAR, and verify the effectiveness of the proposed algorithm through numerical simulation experiments.

Optimization of Medical CT Data with High Precision

AbstractThe precision of medical CT data has an important effect on the CT image reconstruction precision. In this paper, we present a novel approach for optimizing the raw CT data acquired by scanner. The approach can effectively improve the raw CT data precision, and consequently, improve the reconstruction precision. The new approach is based on the fact that the raw CT data can be regarded as the area samples of human density, and the point samples are more accurate than the area samples. The new approach transforms the raw area samples to more accurate point samples to improve the CT data precision by three steps: 1) establish the mapping relationship between area samples and point samples; 2) Segment the raw CT slice into different regions based on the human tissue feature; 3) in each segmented region, construct quadric spline fitting equation with the mapping relationship to transform the area samples to more accurate point samples. Experiments show that the image reconstruction with the new data o...

Permissible Deviation of Rotation Center Based on Fan-Beam Projection ICT System

For ICT wide fan-beam scanning, there is a geometrical supposition that the object rotation center and the radiation source center intersect the image reconstruction center. In practice, the existing intersection deviation has influence on the image reconstruction precision. The image reconstruction mathematical model for shifted rotation center was established, and the relationship between the deviation error and reconstructed image precision was studied by simulation. As a result, for 512×512 CT reconstructed image, there is no distinctive difference between the reference image and the reconstructed image with eccentricity 0.1 pixels; however, with 0.2 pixels or more, the difference is obvious. So, for 512×512 CT image, the maximum permissible deviation of the rotation center is within 0.1 pixel dimension.

Improving Image Quality in Electrical Impedance Tomography (EIT) Using Projection Error Propagation-Based Regularization (PEPR) Technique: A Simulation Study

Abstract A Projection Error Propagation-based Regularization (PEPR) method is proposed and the reconstructed image quality is improved in Electrical Impedance Tomography (EIT). A projection error is produced due to the misfit of the calculated and measured data in the reconstruction process. The variation of the projection error is integrated with response matrix in each iteration and the reconstruction is carried out in EIDORS. The PEPR method is studied with the simulated boundary data for different inhomogeneity geometries. Simulated results demonstrate that the PEPR technique improves image reconstruction precision in EIDORS and hence it can be successfully implemented to increase the reconstruction accuracy in EIT.