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Noniterative sequential weighted least squares algorithm for positron emission tomography reconstruction

✍ Scribed by Jian Zhou; Jean-Louis Coatrieux; Limin Luo


Publisher
Elsevier Science
Year
2008
Tongue
English
Weight
929 KB
Volume
32
Category
Article
ISSN
0895-6111

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✦ Synopsis


This paper proposes a new sequential weighted least squares (SWLS) method for positron emission tomography (PET) reconstruction. The SWLS algorithm is noniterative and can be considered as equivalent to the penalized WLS (PWLS) method under certain initial conditions. However, a full implementation of SWLS is computationally intensive. To overcome this problem, we propose a simplified SWLS as a reasonable alternative to the SWLS. The performance of this SWLS method is evaluated in experiments using both simulated and clinical data. The results show that the method can be advantageously compared with the original SWLS both in computation time and reconstruction quality.


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Maximum Likelihood (ML) estimation based Expectation Maximization (EM) [IEEE Trans Med Imag, MI-1 (2) (1982) 113] reconstruction algorithm has shown to provide good quality reconstruction for positron emission tomography (PET). Our previous work [IEEE Trans Med Imag, 7(4) (1988) 273; Proc IEEE EMBS