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maximum likelihood expectation maximization.
Images were created with an iterative maximum likelihood expectation maximization (MLEM) image reconstruction algorithm.
The images were reconstructed using dedicated maximum likelihood expectation maximization (MLEM) algorithm.
PET data were reconstructed using a maximum likelihood expectation maximization (MLEM) method.
Sinograms were reconstructed using 3D maximum likelihood expectation maximization (3D MLEM) with 30 iterations.
In addition, Maximum Likelihood Expectation Maximization (MLEM) and its accelerated version Ordered Subsets Expectation Maximization (OSEM) algorithms were implemented.
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List-mode maximum likelihood expectation-maximisation (accelerated with ordered subsets [4]) was used for the reconstruction, incorporating the attenuation correction (as a pre-correction to the data) as well as weighted-average sensitivity [2] to achieve a quantitative reconstruction.
In such patients, using the maximum likelihood-expectation maximization (ML-EM) [5] or the ordered subsets-expectation maximization (OS-EM) algorithm [6] is helpful in image reconstruction for controlling the noise.
The images were reconstructed with maximum-likelihood expectation maximization (MLEM).
A rotation-based maximum-likelihood expectation maximization (MLEM) method was used for reconstruction.
The image reconstruction was made with a fully three-dimensional maximum-likelihood expectation maximization (MLEM) algorithm with 20 iterations, without scatter and attenuation correction.
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