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The images were reconstructed iteratively with ordered subset expectation maximisation (2 iterations, 21 subsets, 5 mm Gaussian post-filter), applying all relevant corrections according to the recommendations of the manufacturer, to a 128 × 128 matrix in a 50-cm FOV and fused with unenhanced CT.
SPECT images were iteratively reconstructed (ordered subset expectation maximization,OSEM) and corrected for attenuation using the low-dose CT of the Infinia (no intravenous contrast).
PET images were iteratively reconstructed with ordered subsets expectation maximization (five iterations, eight subsets) with a three-dimensional (3D) Gaussian post-reconstruction smoothing of 5 mm.
The data were reconstructed iteratively using an ordered subset expectation maximization (OSEM) algorithm with 6 iterations and 16 subsets.
The PET images were iteratively reconstructed using ordered subset Syngo Speaking software (Wizard Workstation; Siemens Medical).
PET emission data were reconstructed iteratively using an ordered subset expectation maximisation (OSEM) algorithm with a matrix size of 128 × 128.
Images were reconstructed iteratively (ordered-subset expectation maximisation method, two iterations, eight subsets).
The images were iteratively reconstructed with the ordered subsets expectation maximization algorithm using four iterations with eight subsets and Gaussian filtering of 5 mm FWHM.
Images were iteratively reconstructed using a clinical ordered subset expectation maximization algorithm with CT attenuation correction.
Speciation, extinction and diversification rates through time obtained by iteratively removing orders and higher level clades from the phylogeny.
The tool is able to learn iteratively in order to further refine forecasts as the quality of data available improves.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com