Compressive x-ray material decomposition using structured illumination

Angela P. Cuadros, Xu Ma, Gonzalo R. Arce*

*Corresponding author for this work

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

4 Citations (Scopus)

Abstract

This manuscript explores a new approach for spectral X-ray tomography that uses K-edge filtering structures to attain spectral and spatially coded illumination which enables the acquisition of compressive measurements for the reconstruction of energy-binned images. The system is coined compressive spectral X-ray imaging (CSXI). A multi-stage algorithm is proposed to solve the non-linear ill-posed problem using sparse and low-rank regularization constraints to exploit the structure of the spectral data cube. The proposed algorithm can reconstruct both the energy binned images as well as the material decomposition of the object given a set of basis materials.

Original languageEnglish
Title of host publicationDevelopments in X-Ray Tomography XII
EditorsBert Muller, Ge Wang
PublisherSPIE
ISBN (Electronic)9781510629196
DOIs
Publication statusPublished - 2019
Event12th SPIE Conference on Developments in X-Ray Tomography 2019 - San Diego, United States
Duration: 13 Aug 201915 Aug 2019

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume11113
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

Conference12th SPIE Conference on Developments in X-Ray Tomography 2019
Country/TerritoryUnited States
CitySan Diego
Period13/08/1915/08/19

Keywords

  • K-edge filters
  • Material Decomposition
  • Spectral CT

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