An accelerated and convergent iterative algorithm in image reconstruction

Jianhua Yan; Jun Yu

doi:10.1117/12.741443

1 May 2007 An accelerated and convergent iterative algorithm in image reconstruction

Jianhua Yan, Jun Yu

Proceedings Volume 6534, Fifth International Conference on Photonics and Imaging in Biology and Medicine; 65342Y (2007) https://doi.org/10.1117/12.741443
Event: Fifth International Conference on Photonics and Imaging in Biology and Medicine, 2006, Wuhan, China

Abstract

Positron emission tomography (PET) is becoming increasingly important in the field of medicine and biology. The maximum-likelihood expectation-maximization (ML-EM) algorithm is becoming more important than filtered back-projection (FBP) algorithm which can incorporate various physical models into image reconstruction scheme. However, ML-EM converges slowly. In this paper, we propose a new algorithm named AC-ML-EM (accelerated and convergent maximum likelihood expectation maximization) by introducing gradually decreasing correction factor into ML-EM. AC-ML-EM has a higher speed of convergence. Through the experiments of computer simulated phantom data and real phantom data, AC-ML-EM is shown faster and better quantitatively than conventional ML-EM algorithm.

Citation Download Citation

Jianhua Yan and Jun Yu "An accelerated and convergent iterative algorithm in image reconstruction", Proc. SPIE 6534, Fifth International Conference on Photonics and Imaging in Biology and Medicine, 65342Y (1 May 2007); https://doi.org/10.1117/12.741443

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