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Abstract / Description of output
A total of 169 patients, 139 in the training and 30 in the testing sets were considered. We compared translations at the location of plaques, maximal standard uptake value (SUVmax) and target to background ratio (TBRmax), obtained after observer and automated alignment. Automatic end-to-end registration was performed for 30 patients with 88 coronary vessels and took 95 seconds per patient. Difference in displacement motion vectors between GAN-based and observer-based registration in the x, y and z directions was 0.8 ± 3.0 mm, 0.7 ± 3.0 mm, and 1.7 ± 3.9 mm respectively. TBRmax had a coefficient of repeatability (CR) of 0.31, mean bias of 0.03 and narrow limits of agreement (LOA) (95% LOA: -0.29 to 0.33). SUVmax had CR of 0.26, mean bias of 0 and narrow LOA (95% LOA: -0.26 to 0.26).
In conclusion, pseudo-CT generated by GAN from PET, which are perfectly aligned with PET, can be used to facilitate quick and fully automated registration of PET and CT angiography.
FingerprintDive into the research topics of 'Automated nonlinear registration of coronary PET to CT angiography using pseudo-CT generated from PET with generative adversarial networks'. Together they form a unique fingerprint.
1/02/21 → 31/01/26
1/10/17 → 31/12/18
1/10/16 → 31/03/22