Random-coincidence corrections using iterative reconstruction for PET images

Jyh-Cheng Chen; Ren-Shyan Liu; Kao-Yin Tu; Henry Horng-Shing Lu; Tai-Been Chen; Kuo Liang Chou

doi:10.1117/12.410572

18 December 2000 Random-coincidence corrections using iterative reconstruction for PET images

Jyh-Cheng Chen, Ren-Shyan Liu, Kao-Yin Tu, Henry Horng-Shing Lu, Tai-Been Chen, Kuo Liang Chou

Proceedings Volume 4142, Penetrating Radiation Systems and Applications II; (2000) https://doi.org/10.1117/12.410572
Event: International Symposium on Optical Science and Technology, 2000, San Diego, CA, United States

Abstract

Iterative reconstruction (IR) algorithms can reduce artifacts caused by filtered backprojection (FBP) or convolution backprojection (CBP). Recently, the computational effects required for IR of positron emission tomography (PET) studies have been reduced to make it practically appealing. We have made an implementation of the improved maximum likelihood-expectation maximization (ML-EM) algorithm. The transition matrix was generated based on the geometry of the instrument. Phantoms of 6 line sources and 19 line sources were used to test our accelerated ML-EM algorithms against the FBP method. The singles were used to calculate the random coincidence rates by a well known formula and were compared to the randoms obtained by another geometric method. We also designed a new model using two line sources to determine the ratio of random events to true events. The artifacts near those line sources were eliminated with the ML-EM method. With decay correction, the RC events were uniformity distributed in whole field after 10 iterations. The ML-EM reconstructed images are superior to those obtained with FBP. The patterns of randoms provide insightful information for random correction, which the hardware correction by the delay window can not provide. This information is particularly valuable when the delay window correction is not available in the old fashion PET scanner.

Citation Download Citation

Jyh-Cheng Chen, Ren-Shyan Liu, Kao-Yin Tu, Henry Horng-Shing Lu, Tai-Been Chen, and Kuo Liang Chou "Random-coincidence corrections using iterative reconstruction for PET images", Proc. SPIE 4142, Penetrating Radiation Systems and Applications II, (18 December 2000); https://doi.org/10.1117/12.410572

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KEYWORDS

Positron emission tomography

Reconstruction algorithms

Sensors

Expectation maximization algorithms

Scanners

Signal attenuation

Convolution

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