A Convex Reconstruction Model for X-ray Tomographic Imaging with Uncertain Flat-fields

Hari Om Aggrawal*, Martin Skovgaard Andersen, Sean Rose, Emil Y. Sidky

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Classical methods for X-ray computed tomography are based on the assumption that the X-ray source intensity is known, but in practice, the intensity is measured and hence uncertain. Under normal operating conditions, when the exposure time is sufficiently high, this kind of uncertainty typically has a negligible effect on the reconstruction quality. However, in time- or dose-limited applications such as dynamic CT, this uncertainty may cause severe and systematic artifacts known as ring artifacts. By carefully modeling the measurement process and by taking uncertainties into account, we derive a new convex model that leads to improved reconstructions despite poor quality measurements. We demonstrate the effectiveness of the methodology based on simulated and real datasets.
Original languageEnglish
JournalI E E E Transactions on Computational Imaging
Issue number1
Pages (from-to)17-31
Publication statusPublished - 2018


  • X-ray computed tomography
  • Ring artifacts
  • Low intensity
  • Reconstruction methods

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