Laser & Optoelectronics Progress, Volume. 59, Issue 23, 2310001(2022)

Tomographic Image Reconstruction Method Combining Exponential Filtering Inverse Projection Reconstruction and Iterative Reconstruction Algorithms

Qianghua Chen1、*, Jinhong Ding1, Sheng Zhou1, Wenyuan Han1, Lü Hongbo1, Qiguo Sun1, Xiangyue Kong2, and Huifu Luo3
Author Affiliations
  • 1School of Mechanical and Materials Engineering, North China University of Technology, Beijing 100144, China
  • 2The 11th Research Institute of China Electronics Technology Corporation, Beijing 100016, China
  • 3School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China
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    An iterative exponential filtering(EF) inverse projection reconstruction algorithm is proposed for data reconstruction in the field of optical tomography. The proposed algorithm combines the advantages of the high reconstruction quality of iterative reconstruction algorithm and high reconstruction speed of the EF inverse projection reconstruction algorithm. The filter function adopts the exponential function, and therefore, its antinoise performance is better than those of traditional filter functions. The algorithm adopts the normalized mean square distance d and normalized mean absolute distance r between the reconstructed and real images as the optimization goals. In addition, it adjusts the filter function exponential factor to reduce the impact of projection data noise and establishes an iterative calculation model. The simulation experiments show that the EF function has better reconstruction accuracy than traditional functions. The image reconstruction quality of the proposed algorithm is higher than that of the EF inverse projection reconstruction algorithm, r decreases by 20%. A refractive index optical tomography is conducted. The refractive index reconstruction of the measured data is performed using the proposed algorithm and EF inverse projection reconstruction algorithm. The reconstruction results are then compared with the calibration results obtained using the instrument. The results show that the proposed algorithm exhibits high reconstruction accuracy, and that the maximum error with the calibration results obtained using the instrument is 7.9×10-6. Compared with the EF inverse projection reconstruction algorithm, the reconstruction accuracy of the proposed method is improved by approximately 21%.

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    Qianghua Chen, Jinhong Ding, Sheng Zhou, Wenyuan Han, Lü Hongbo, Qiguo Sun, Xiangyue Kong, Huifu Luo. Tomographic Image Reconstruction Method Combining Exponential Filtering Inverse Projection Reconstruction and Iterative Reconstruction Algorithms[J]. Laser & Optoelectronics Progress, 2022, 59(23): 2310001

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    Paper Information

    Category: Image Processing

    Received: Feb. 24, 2022

    Accepted: Jun. 13, 2022

    Published Online: Nov. 28, 2022

    The Author Email: Chen Qianghua (chenqianghua@tsinghua.org.cn)

    DOI:10.3788/LOP202259.2310001

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