Core Imaging Library - Part II: multichannel reconstruction for dynamic and spectral tomography

Evangelos Papoutsellis*, Evelina Ametova, Claire Delplancke, Gemma Fardell, Jakob Sauer Jørgensen, Edoardo Pasca, Martin Turner, Ryan Warr, William R.B. Lionheart, Philip J. Withers

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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The newly developed core imaging library (CIL) is a flexible plug and play library for tomographic imaging with a specific focus on iterative reconstruction. CIL provides building blocks for tailored regularized reconstruction algorithms and explicitly supports multichannel tomographic data. In the first part of this two-part publication, we introduced the fundamentals of CIL. This paper focuses on applications of CIL for multichannel data, e.g. dynamic and spectral. We formalize different optimization problems for colour processing, dynamic and hyperspectral tomography and demonstrate CIL's capabilities for designing state-of-the-art reconstruction methods through case studies and code snapshots. This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 2'.

Original languageEnglish
Article number20200193
JournalPhilosophical transactions. Series A, Mathematical, physical, and engineering sciences
Issue number2204
Number of pages30
Publication statusPublished - 23 Aug 2021


  • Computed tomography
  • Inverse problems
  • Iterative reconstruction
  • Magnetic resonance imaging (MRI)
  • Materials science
  • Positron emission tomography (PET)
  • Sparse CT
  • X-ray CT


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