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Simultaneous 3-dimensional resolution correction in SPECT reconstruction with an ordered-subsets expectation maximization algorithm.

Simultaneous 3-dimensional resolution correction in SPECT reconstruction with an ordered-subsets expectation maximization algorithm.
Collimators are used for the improvement of information about the positions of sources by limiting the incidence direction of gamma-rays and characteristic x-rays to detectors. In this study, we attempted to improve the spatial resolution of (201)Tl myocardial SPECT by using simultaneous 3-dimensional distance-dependent resolution correction (DRC) incorporated into the ordered-subsets expectation maximization algorithm.Simulation was performed with various sizes of balls, and measurement with a line-source phantom was performed at different source-detector distances. Imaging of a hot-rod phantom, the defect area of a myocardial phantom, and the myocardial thickness and cardiac lumen in a human study by (201)TlCl myocardial SPECT was evaluated before and after DRC.We performed simulation by using 5 sizes of balls and found marked improvement in resolution in all x-, y-, and z-axis directions. In the line-source phantom, when the radial distance was very long (30.5 cm), the correction effects were slightly low. However, when the distance was similar to the clinically used rotation radius (22.5 cm), the correction effects were good in the hot-rod and myocardial phantoms and in the human study.DRC markedly improved the spatial resolution of SPECT images, suggesting that this method is useful for the quantification of infarcted areas by myocardial SPECT.
Male, Tomography, Emission-Computed, Single-Photon, Likelihood Functions, Reproducibility of Results, Heart, Middle Aged, Image Enhancement, Sensitivity and Specificity, Imaging, Three-Dimensional, Image Interpretation, Computer-Assisted, Humans, Algorithms
Male, Tomography, Emission-Computed, Single-Photon, Likelihood Functions, Reproducibility of Results, Heart, Middle Aged, Image Enhancement, Sensitivity and Specificity, Imaging, Three-Dimensional, Image Interpretation, Computer-Assisted, Humans, Algorithms
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