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Vector Extrapolated Fast Maximum Likelihood Estimation Algorithm For Emission Tomography

Rajeevan, N and Rajgopal, K and Krishna, G (1992) Vector Extrapolated Fast Maximum Likelihood Estimation Algorithm For Emission Tomography. In: IEEE Transactions on Medical Imaging, 11 (1). pp. 9-20.


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A new class of fast maximum likelihood estimation (MLE) algorithms for emission computed tomography (ECT) is developed. In these cyclic iterative algorithms, vector extrapolation techniques are integrated with the iterations in gradient-based MLE algorithms, with the objective of accelerating the convergence of the base iterations. This results in a substantial reduction in the effective number of base iterations required for obtaining an emission density estimate of specified quality. The mathematical theory behind the minimal polynomial and reduced rank vector extrapolation techniques, in the context of emission tomography, is presented. With the EM and EM search algorithms in the base iterations, these extrapolation techniques are implemented in a positron emission tomography system. Using computer experiments, with measurements taken from simulated phantoms, the new algorithms are evaluated. It is shown that, with minimal additional computations, the proposed approach results in substantial improvement in reconstruction, in terms of both qualitative visual performance and quantitative measures of likelihood and residual error, of the image.

Item Type: Journal Article
Publication: IEEE Transactions on Medical Imaging
Publisher: IEEE
Additional Information: ©1992 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Department/Centre: Division of Electrical Sciences > Electrical Engineering
Date Deposited: 25 Aug 2008
Last Modified: 19 Sep 2010 04:13
URI: http://eprints.iisc.ac.in/id/eprint/522

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