Three-dimensional iterative reconstruction of pulsed radiation sources using spherical harmonic decomposition.

Jianpeng Gao, Liang Sheng, Baojun Duan, Xinyi Wang, Dongwei Hei, Huaibi Chen
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Abstract

Neutron and x-ray imaging are essential ways to diagnose a pulsed radiation source. The three-dimensional (3D) intensity distribution reconstructed from two-dimensional (2D) radiation images can significantly promote research regarding the generation and variation mechanisms of pulsed radiation sources. Only a few (≤5) projected images at one moment are available due to the difficulty in building imaging systems for high-radiation-intensity and short-pulsed sources. The reconstruction of a 3D source with a minimal number of 2D images is an ill-posed problem that leads to severe structural distortions and artifacts of the image reconstructed by conventional algorithms. In this paper, we present an iterative method to reconstruct a 3D source using spherical harmonic decomposition. Our algorithm improves the representation ability of spherical harmonic decomposition for 3D sources by enlarging the order of the expansion, which is limited in current analytical reconstruction algorithms. Prior knowledge of the source can be included to obtain a reasonable solution. Numerical simulations demonstrate that the reconstructed image quality of the iterative algorithm is better than that of the analytical algorithm. The iterative method can suppress the effect of noise in the integral projection image and has better robustness and adaptability than the analytical method.

基于球谐分解的脉冲辐射源三维迭代重建。
中子和x射线成像是诊断脉冲辐射源的基本方法。由二维辐射图像重建的三维辐射强度分布对脉冲辐射源产生和变化机制的研究具有重要的推动作用。由于构建高辐射强度和短脉冲光源成像系统的困难,在同一时刻只有少数(≤5)个投影图像可用。用最少数量的二维图像重建三维源是一个病态问题,它会导致严重的结构扭曲和传统算法重建的图像伪影。本文提出了一种利用球谐分解迭代重建三维源的方法。该算法通过增大展开的阶数来提高三维源的球面谐波分解的表示能力,这是目前解析重构算法所存在的局限性。可以包括源的先验知识,以获得合理的解决方案。数值模拟结果表明,迭代算法的重构图像质量优于解析算法。迭代法可以抑制积分投影图像中噪声的影响,比解析法具有更好的鲁棒性和适应性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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