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Comparison between ML-EM and WLS-CG algorithms for SPECT image reconstruction

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TLDR
The convergence rate of the weighted least squares with conjugate gradient (WLS-CG) algorithm is about ten times that of the maximum likelihood with expectation maximization (ML-EM) algorithm.
Abstract
The properties of the maximum likelihood with expectation maximization (ML-EM) and the weighted least squares with conjugate gradient (WLS-CG) algorithms for use in compensation for attenuation and detector response in cardiac SPECT imaging were studied. A realistic phantom, derived from a patient X-ray CT study to simulate /sup 201/Tl SPECT data, was used in the investigation. In general, the convergence rate of the WLS-CG algorithm is about ten times that of the ML-EM algorithm. Also, the WLS-CG exhibits a faster increase in image noise at large iteration numbers than the ML-EM algorithm. >

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Citations
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Efficient fully 3-D iterative SPECT reconstruction with Monte Carlo-based scatter compensation

TL;DR: A computationally efficient fully 3-D MCS-based reconstruction architecture is developed by combining the following methods: a dual matrix ordered subset (DM-OS) reconstruction algorithm to accelerate the reconstruction and avoid massive transition matrix precalculation and storage.
Journal ArticleDOI

Maximum likelihood, least squares, and penalized least squares for PET

TL;DR: It is shown that the same scaled steepest descent algorithm can be applied to the least squares merit function, and that it can be accelerated using the conjugate gradient approach.
Journal ArticleDOI

The importance and implementation of accurate 3D compensation methods for quantitative SPECT.

TL;DR: 3D implementation of the quantitative compensation methods provides the best SPECT image in terms of quantitative accuracy, spatial resolution, and noise at a cost of high computational requirements.
Journal ArticleDOI

Quantitative cardiac SPECT reconstruction with reduced image degradation due to patient anatomy

TL;DR: It is concluded that reconstruction methods which accurately compensate for nonuniform attenuation can substantially reduce image degradation caused by variations in patient anatomy in cardiac SPECT.
Journal ArticleDOI

Transmission maximum-likelihood reconstruction with ordered subsets for cone beam CT.

TL;DR: With ordered subsets, high-quality iterative reconstruction is now available in clinically practical reconstructions times, and the existing transmission maximum-likelihood algorithm (TRML) is accurate but the reconstruction time is too long.
References
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