Paper
11 March 2005 Multigrid inversion algorithms for Poisson noise model-based tomographic reconstruction
Author Affiliations +
Proceedings Volume 5674, Computational Imaging III; (2005) https://doi.org/10.1117/12.598771
Event: Electronic Imaging 2005, 2005, San Jose, California, United States
Abstract
A multigrid inversion approach is proposed to solve Poisson noise model-based inverse problems. The algorithm works by moving up and down in resolution with a set of coarse scale cost functions, which incorporates a coarse scale Poisson mean defined in low resolution data and image spaces. Applications of the approach to Bayesian reconstruction algorithms in transmission and emission tomography are presented. Simulation results indicate that the proposed multigrid approach results in significant improvement in convergence speed compared to the fixed-grid iterative coordinate descent (ICD) method.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Seungseok Oh, Charles A. Bouman, and Kevin J. Webb "Multigrid inversion algorithms for Poisson noise model-based tomographic reconstruction", Proc. SPIE 5674, Computational Imaging III, (11 March 2005); https://doi.org/10.1117/12.598771
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KEYWORDS
Reconstruction algorithms

Tomography

Data modeling

Data conversion

Model-based design

Infrared imaging

Magnesium

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