Sparse-view X-ray spectral CT reconstruction using annihilating filter-based low rank hankel matrix approach

Yo Seob Han, Kyong Hwan Jin, Kyungsang Kim, Jong Chul Ye

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

7 Scopus citations

Abstract

In a kVp switching-based sparse view spectral CT, each spectral image cannot be reconstructed separably by an analytic reconstruction method, because the projection views for each spectral band is too sparse. However, the underlying structure is common between the spectral bands, so there exists inter-spectral redundancies that can be exploited by the recently proposed annihilating filter-based low rank Hankel matrix approach (ALOHA). More specifically, the sparse view projection data are first rebinned in the Fourier space, from which Hankel structured matrix with missing elements are constructed for each spectral band. Thanks to the inter-spectral correlations as well as transform domain sparsity of underlying images, the concatenated Hankel structured matrix is low-ranked, and the missing Fourier data for each spectral band can be simultaneously estimated using a low rank matrix completion. To reduce the computational complexity furthermore, we exploit the Hermitian symmetry of Fourier data. Numerical experiments confirm that the proposed method outperforms the existing ones.

Original languageEnglish
Title of host publication2016 IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro, ISBI 2016 - Proceedings
PublisherIEEE Computer Society
Pages573-576
Number of pages4
ISBN (Electronic)9781479923502
DOIs
StatePublished - 15 Jun 2016
Event2016 IEEE 13th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016 - Prague, Czech Republic
Duration: 13 Apr 201616 Apr 2016

Publication series

NameProceedings - International Symposium on Biomedical Imaging
Volume2016-June
ISSN (Print)1945-7928
ISSN (Electronic)1945-8452

Conference

Conference2016 IEEE 13th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016
Country/TerritoryCzech Republic
CityPrague
Period13/04/1616/04/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Keywords

  • annihilating filter
  • low rank Hankel matrix
  • sparse-view X-ray CT
  • spectral computed tomography (CT)

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