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Accelerating SAGE algorithm in PET image reconstruction by rescaled block-iterative method 被引量:1
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作者 朱宏擎 舒华忠 +1 位作者 周健 罗立民 《Journal of Southeast University(English Edition)》 EI CAS 2005年第2期207-210,共4页
A new method to accelerate the convergent rate of the space-alternatinggeneralized expectation-maximization (SAGE) algorithm is proposed. The new rescaled block-iterativeSAGE (RBI-SAGE) algorithm combines the RBI algo... A new method to accelerate the convergent rate of the space-alternatinggeneralized expectation-maximization (SAGE) algorithm is proposed. The new rescaled block-iterativeSAGE (RBI-SAGE) algorithm combines the RBI algorithm with the SAGE algorithm for PET imagereconstruction. In the new approach, the projection data is partitioned into disjoint blocks; eachiteration step involves only one of these blocks. SAGE updates the parameters sequentially in eachblock. In experiments, the RBI-SAGE algorithm and classical SAGE algorithm are compared in theapplication on positron emission tomography (PET) image reconstruction. Simulation results show thatRBI-SAGE has better performance than SAGE in both convergence and image quality. 展开更多
关键词 positron emission tomography space-alternating generalizedexpectation-maximization image reconstruction rescaled block-iterative maximum likelihood
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