Artifacts and Visible Singularities in Limited Data X-Ray Tomography

Todd Quinto

Research output: Contribution to journalJournal articleResearchpeer-review

275 Downloads (Pure)


We describe a principle to determine which features of an object will be easy to reconstruct from limited X-ray CT data and which will be difficult. The principle depends on the geometry of the data set, and it applies to any limited data set. We also describe a characterization of Frikel and the author explaining artifacts that can be added to limited angle reconstructions, and we provide an easy-to-implement method to decrease them. These ideas are justified using microlocal analysis, deep mathematics that involves Fourier theory. Reconstructions from simulated and real limited data are given to illustrate our ideas.
Original languageEnglish
JournalSensing and Imaging
Issue number1
Number of pages14
Publication statusPublished - 2017


  • Engineering
  • Electrical Engineering
  • Microwaves, RF and Optical Engineering
  • Imaging / Radiology
  • SC8
  • X-ray tomography
  • Limited tomographic data
  • Artifacts
  • Microlocal analysis
  • Instrumentation
  • Electrical and Electronic Engineering
  • Functional analysis
  • Imaging systems
  • Repair
  • Tomography
  • Fourier theory
  • Limited data
  • Limited data sets
  • Limited-angle reconstruction
  • Tomographic data
  • Computerized tomography


Dive into the research topics of 'Artifacts and Visible Singularities in Limited Data X-Ray Tomography'. Together they form a unique fingerprint.

Cite this