Generalized algebraic reconstruction techniques

Yibin Zheng, Heng Li

Research output: Contribution to journalConference articlepeer-review


We propose a family of new algorithms that can be viewed as a generalization of the Algebraic Reconstruction Techniques (ART). These algorithms can be tailored for trade-offs between convergence speed and memory requirement. They also can be made to include Gaussian a priori image models. A key advantage is that they can handle arbitrary data acquisition scheme. Approximations are required for practical sized image reconstruction. We discuss several approximations and demonstrate numerical simulation examples for computed tomography (CT) reconstructions.

Original languageEnglish (US)
Pages (from-to)19-25
Number of pages7
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - Dec 1 2002
Externally publishedYes
EventImage Reconstruction from Incomplete Data II - Seattle, WA, United States
Duration: Jul 8 2002Jul 9 2002


  • Algebraic reconstruction techniques
  • Recursive least squares
  • Tomography

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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