Journal ArticleDOI
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. >read more
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.
Benjamin M. W. Tsui,Eric C. Frey,X.D. Zhao,David S. Lalush,R.E. Johnston,William H. McCartney +5 more
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
Benjamin M. W. Tsui,X.D. Zhao,G.K. Gregoriou,D.S. Lalushl,Eric C. Frey,R.E. Johnston,William H. McCartney +6 more
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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Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
Stuart Geman,Donald Geman +1 more
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Algebraic Reconstruction Techniques (ART) for three-dimensional electron microscopy and X-ray photography
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EM reconstruction algorithms for emission and transmission tomography.
Kenneth Lange,Richard E. Carson +1 more
TL;DR: The general principles behind all EM algorithms are discussed and in detail the specific algorithms for emission and transmission tomography are derived and the specification of necessary physical features such as source and detector geometries are discussed.
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Bayesian reconstructions from emission tomography data using a modified EM algorithm
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