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Proceedings Paper

Globally defined MAP method for PET image reconstruction
Author(s): Yining Hu; Jian Zhou; Limin Luo
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Paper Abstract

In this paper, we proposed a new MAP method more suitable for low signal to noise (SNR) measurements. We took the projection space as a Gibbs random field, under such assumption, new priori was defined which is not limited to a small neighborhood region. We choose the hyperparameter of the penalty using maximum-likelihood estimation. We applied filtering scheme in the proposed method to control reconstruction results. The proposed method was applied to reconstruct both simulated data and real clinical data, and the results are discussed. Future work is mentioned at the end of the paper.

Paper Details

Date Published: 14 November 2007
PDF: 8 pages
Proc. SPIE 6789, MIPPR 2007: Medical Imaging, Parallel Processing of Images, and Optimization Techniques, 67890G (14 November 2007); doi: 10.1117/12.747663
Show Author Affiliations
Yining Hu, Southeast Univ. (China)
Jian Zhou, Lab. Traitement du Signal et de l'Image-INSERM, Univ. de Rennes 1,Univ. de Rennes 1 (United States)
Limin Luo, Southeast Univ. (China)


Published in SPIE Proceedings Vol. 6789:
MIPPR 2007: Medical Imaging, Parallel Processing of Images, and Optimization Techniques

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