Iterative image reconstruction with random correction for PET studies

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

doi:10.1117/12.387629

6 June 2000 Iterative image reconstruction with random correction for PET studies

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

Author Affiliations +

Proceedings Volume 3979, Medical Imaging 2000: Image Processing; (2000) https://doi.org/10.1117/12.387629
Event: Medical Imaging 2000, 2000, San Diego, CA, United States

Abstract

A maximum likelihood-expectation maximization (ML-EM) reconstruction algorithm has been developed that allows random coincidence correction for the phantom we used and the reconstructed images are better than those obtained by convolution backprojection (CBP) for positron emission tomography (PET) studies in terms of spatial resolution, image artifacts and noise. With our algorithm reconstruct the true coincidence events and random coincidence events were reconstructed separately. We also calculated the random ratio from the measured projection data (singles) using line and cylindrical phantoms, respectively. From cylindrical phantom experiments, the random event ratio was 41.8% to 49.1% in each ring. These results are close to the ratios obtained from geometric calculation, which range from 45.0% to 49.5%. The random ratios and the patterns of random events provide insightful information for random correction. This information is particularly valuable when the delay window correction is not available as in the case of our PET system.

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Jyh-Cheng Chen, Jyh-Cheng Chen, Ren-Shyan Liu, Ren-Shyan Liu, Kao-Yin Tu, Kao-Yin Tu, Henry Horng-Shing Lu, Henry Horng-Shing Lu, Tai-Been Chen, Tai-Been Chen, Kuo Liang Chou, Kuo Liang Chou, } "Iterative image reconstruction with random correction for PET studies", Proc. SPIE 3979, Medical Imaging 2000: Image Processing, (6 June 2000); doi: 10.1117/12.387629; https://doi.org/10.1117/12.387629

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