Display options
Cite
Wang D, Hu H, Zhang F, et al. Source reconstruction for neutron coded-aperture imaging: A sparse method. Rev Sci Instrum. 2017;88(8):083502doi: 10.1063/1.4996193.
Wang, D., Hu, H., Zhang, F., & Jia, Q. (2017). Source reconstruction for neutron coded-aperture imaging: A sparse method. The Review of scientific instruments, 88(8), 083502. https://doi.org/10.1063/1.4996193
Wang, Dongming, et al. "Source reconstruction for neutron coded-aperture imaging: A sparse method." The Review of scientific instruments vol. 88,8 (2017): 083502. doi: https://doi.org/10.1063/1.4996193
Wang D, Hu H, Zhang F, Jia Q. Source reconstruction for neutron coded-aperture imaging: A sparse method. Rev Sci Instrum. 2017 Aug;88(8):083502. doi: 10.1063/1.4996193. PMID: 28863656.
Copy Download .nbib Format: NLM
Share it on

Rev Sci Instrum. 2017 Aug;88(8):083502. doi: 10.1063/1.4996193.

Source reconstruction for neutron coded-aperture imaging: A sparse method.

The Review of scientific instruments

Dongming Wang, Huasi Hu, Fengna Zhang, Qinggang Jia

Affiliations

  1. School of Energy and Power Engineering, Xi'an Jiaotong University, Xi'an 710049, China.
  2. Institute of Applied Physics and Computational Mathematics, Beijing 100094, China.

PMID: 28863656 DOI: 10.1063/1.4996193

Abstract

Neutron coded-aperture imaging has been developed as an important diagnostic for inertial fusion studies in recent decades. It is used to measure the distribution of neutrons produced in deuterium-tritium plasma. Source reconstruction is an essential part of the coded-aperture imaging. In this paper, we applied a sparse reconstruction method to neutron source reconstruction. This method takes advantage of the sparsity of the source image. Monte Carlo neutron transport simulations were performed to obtain the system response. An interpolation method was used while obtaining the spatially variant point spread functions on each point of the source in order to reduce the number of point spread functions that needs to be calculated by the Monte Carlo method. Source reconstructions from simulated images show that the sparse reconstruction method can result in higher signal-to-noise ratio and less distortion at a relatively high statistical noise level.

Publication Types