Calculation of projection matrix in image reconstruction based on neural network

Bingzhen Lei, Xiuqing Li, Jun Zhang, Junhai Wen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

The iterative reconstruction algorithms can get better reconstruction result by adding constraints in the case of incomplete or uneven projection. In the iterative reconstruction algorithm, how to obtain the relationship between the reconstructed image and the projected data, namely, projection matrix, is the key to the image reconstruction. In this paper, the neural network algorithm is used to calculate the projection matrix, which gives a solution to a class of problems. In simulation, we use the projection matrix trained by the neural network to achieve the reconstruction, and the results show that the original image can be well reconstructed.

Original languageEnglish
Title of host publicationProceedings - 3rd International Conference on Computational Intelligence and Applications, ICCIA 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages166-170
Number of pages5
ISBN (Electronic)9780769565286
DOIs
Publication statusPublished - 2 Jul 2018
Event3rd International Conference on Computational Intelligence and Applications, ICCIA 2018 - Hong Kong, China
Duration: 28 Jul 201830 Jul 2018

Publication series

NameProceedings - 3rd International Conference on Computational Intelligence and Applications, ICCIA 2018

Conference

Conference3rd International Conference on Computational Intelligence and Applications, ICCIA 2018
Country/TerritoryChina
CityHong Kong
Period28/07/1830/07/18

Keywords

  • ART algorithm
  • Iterative reconstruction
  • Neural network
  • Projection matrix
  • Pseudo inverse

Fingerprint

Dive into the research topics of 'Calculation of projection matrix in image reconstruction based on neural network'. Together they form a unique fingerprint.

Cite this