Deep learning–based time-of-flight (ToF) image enhancement of non-ToF PET scans.

Purpose: To improve the quantitative accuracy and diagnostic confidence of PET images reconstructed without time-of-flight (ToF) using deep learning models trained for ToF image enhancement (DL-ToF). Methods: A total of 273 [18F]-FDG PET scans were used, including data from 6 centres equipped with G...

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Bibliographic Details
Published in:European Journal of Nuclear Medicine & Molecular Imaging Vol. 49; no. 11; pp. 3740 - 3750
Main Authors: Mehranian, Abolfazl, Wollenweber, Scott D., Walker, Matthew D., Bradley, Kevin M., Fielding, Patrick A., Huellner, Martin, Kotasidis, Fotis, Su, Kuan-Hao, Johnsen, Robert, Jansen, Floris P., McGowan, Daniel R.
Format: Journal Article
Published: Springer Nature Sep2022
Online Access:View this record in EBSCOhost