2013
DOI: 10.1109/tns.2013.2278759
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Comparison of 4-Class and Continuous Fat/Water Methods for Whole-Body, MR-Based PET Attenuation Correction

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Cited by 79 publications
(48 citation statements)
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“…The last nine time points from 5 minutes to 30 minutes on the postinjection images were used to determine the slope by means of linear regression in the Patlak graphical analysis (23). As representative kinetic parameters reflecting FCH influx, the average and maximum K1 in the one-tissue compartment model and the K i (net influx fat and water method was used (20). PET images were then reconstructed into dynamic multiframes (6 3 10 sec, 8 3 30 sec, 5 3 1 min, and 4 3 5 min) with a matrix size of 128 3 128 (voxel size, 2.34 3 2.34 3 2.78 mm; transaxial field of view, 30 cm).…”
Section: Resultsmentioning
confidence: 99%
“…The last nine time points from 5 minutes to 30 minutes on the postinjection images were used to determine the slope by means of linear regression in the Patlak graphical analysis (23). As representative kinetic parameters reflecting FCH influx, the average and maximum K1 in the one-tissue compartment model and the K i (net influx fat and water method was used (20). PET images were then reconstructed into dynamic multiframes (6 3 10 sec, 8 3 30 sec, 5 3 1 min, and 4 3 5 min) with a matrix size of 128 3 128 (voxel size, 2.34 3 2.34 3 2.78 mm; transaxial field of view, 30 cm).…”
Section: Resultsmentioning
confidence: 99%
“…Axial slices were reconstructed at a 2.78-mm thickness. Attenuation was corrected using a 2-echo Dixon fat-water separation algorithm for the body, whereas the lung was segmented using a region-growing algorithm provided with the scanner (16).…”
Section: Human Experimentsmentioning
confidence: 99%
“…Quantitative corrections applied during image reconstruction included normalization, dead time, point-spread function, randoms, scatter, decay, and attenuation. The latter was based on a four-tissue-class (air, lung, fat, and soft tissue) segmented attenuation map, automatically generated from the results of the MR-based attenuation correction acquisition (Lava Flex; GE Healthcare) (13). The attenuation coefficients for air (0 cm…”
Section: Data Processingmentioning
confidence: 99%