English

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

Numerical Analysis 2017-07-17 v1 Applications

Abstract

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 data sets.

Keywords

Cite

@article{arxiv.1707.04531,
  title  = {A Convex Reconstruction Model for X-ray Tomographic Imaging with Uncertain Flat-fields},
  author = {Hari Om Aggrawal and Martin Skovgaard Andersen and Sean Rose and Emil Y. Sidky},
  journal= {arXiv preprint arXiv:1707.04531},
  year   = {2017}
}

Comments

Accepted at IEEE Transactions on Computational Imaging

R2 v1 2026-06-22T20:47:20.148Z