Paper
14 November 2007 Globally defined MAP method for PET image reconstruction
Yining Hu, Jian Zhou, Limin Luo
Author Affiliations +
Proceedings Volume 6789, MIPPR 2007: Medical Imaging, Parallel Processing of Images, and Optimization Techniques; 67890G (2007) https://doi.org/10.1117/12.747663
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China
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.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yining Hu, Jian Zhou, and Limin Luo "Globally defined MAP method for PET image reconstruction", Proc. SPIE 6789, MIPPR 2007: Medical Imaging, Parallel Processing of Images, and Optimization Techniques, 67890G (14 November 2007); https://doi.org/10.1117/12.747663
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Cited by 1 scholarly publication.
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KEYWORDS
Image filtering

Positron emission tomography

Image restoration

Reconstruction algorithms

Photon counting

Signal to noise ratio

Image analysis

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