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Proceedings Paper

Fast conjugate gradient algorithm extension for analyzer-based imaging reconstruction
Author(s): Oriol Caudevilla; Jovan G. Brankov
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Paper Abstract

This paper presents an extension of the classic Conjugate Gradient Algorithm. Motivated by the Analyzer-Based Imaging inverse problem, the novel method maximizes the Poisson regularized log-likelihood with a non-linear transformation of parameter faster than other solutions. The new approach takes advantage of the special properties of the Poisson log-likelihood to conjugate each ascend direction with respect all the previous directions taken by the algorithm. Our solution is compared with the general solution for non-quadratic unconstrained problems: the Polak- Ribiere formula. Both methods are applied to the ABI reconstruction problem.

Paper Details

Date Published: 1 April 2016
PDF: 6 pages
Proc. SPIE 9783, Medical Imaging 2016: Physics of Medical Imaging, 97834J (1 April 2016); doi: 10.1117/12.2217164
Show Author Affiliations
Oriol Caudevilla, Illinois Institute of Technology (United States)
Jovan G. Brankov, Illinois Institute of Technology (United States)


Published in SPIE Proceedings Vol. 9783:
Medical Imaging 2016: Physics of Medical Imaging
Despina Kontos; Thomas G. Flohr, Editor(s)

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