Reconstruction of the Attenuated Radon Transform in π-Scheme Short-Scan Spect

Shi, Tingting; Wang, Jinping

doi:10.1016/s0252-9602(13)60109-5

Cited by 5 publications

(1 citation statement)

References 13 publications

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“…Some of the iterative algorithms have involved evaluation of certain analytic inversion formulae as a part of the method. Analytic algorithms could exactly reconstruct the object function by explicit inversion formulas (all kinds of different methods see [15][16][17][18][19][20][21][22][23]).…”

Section: Introductionmentioning

confidence: 99%

Convergence analysis of an accelerated expectation‐maximization algorithm for ill‐posed integral equations

Geng

Wang

2015

Math Methods in App Sciences

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The maximum-likelihood expectation-maximization (EM) algorithm has attracted considerable interest in single-photon emission computed tomography, because it produces superior images in addition to be being flexible, simple, and allowing a physical interpretation. However, it often needs a large number of calculations because of the algorithm's slow rate of convergence. Therefore, there is a large body of literature concerning the EM algorithm's acceleration. One of the accelerated means is increasing an overrelaxation parameter, whereas we have not found any analysis in this method that would provide an immediate answer to the questions of the convergence. In this paper, our main focus is on the continuous version of an accelerated EM algorithm based on Lewitt and Muehllenner. We extend their conclusions to the infinitedimensional space and interpret and analyze the convergence of the accelerated EM algorithm. We also obtain some new properties of the modified algorithm.

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