AIR Tools II: algebraic iterative reconstruction methods, improved implementation

Per Christian Hansen, Jakob Sauer Jørgensen

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Abstract

We present a MATLAB software package with efficient, robust, and flexible implementations of algebraic iterative reconstruction (AIR) methods for computing regularized solutions to discretizations of inverse problems. These methods are of particular interest in computed tomography and similar problems where they easily adapt to the particular geometry of the problem. All our methods are equipped with stopping rules as well as heuristics for computing a good relaxation parameter, and we also provide several test problems from tomography. The package is intended for users who want to experiment with algebraic iterative methods and their convergence properties. The present software is a much expanded and improved version of the package AIR Tools from 2012, based on a new modular design. In addition to improved performance and memory use, we provide more flexible iterative methods, a column-action method, new test problems, new demo functions, and—perhaps most important—the ability to use function handles instead of (sparse) matrices, allowing larger problems to be handled.
Original languageEnglish
JournalNumerical Algorithms
Pages (from-to)1-31
Number of pages31
ISSN1017-1398
DOIs
Publication statusPublished - 2017

Keywords

  • Applied Mathematics
  • Algebraic iterative reconstruction
  • ART methods
  • Column-action methods
  • Semi-convergence
  • SIRT methods
  • Stopping rules
  • Tomographic imaging

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