Investigation of PET image quality with acquisition time/bed and enhancement of lesion quantification accuracy through deep progressive learning

Investigation of PET image quality with acquisition time/bed and enhancement of lesion quantification accuracy through deep progressive learning

Abstract Objective To improve the PET image quality by a deep progressive learning (DPL) reconstruction algorithm and evaluate the DPL performance in lesion quantification. Methods We reconstructed PET images from 48 oncological patients using ordered subset expectation maximization (OSEM) and deep...

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Bibliographic Details
Main Authors: Hongxing Yang, Shihao Chen, Ming Qi, Wen Chen, Qing Kong, Jianping Zhang, Shaoli Song
Format: Article
Language:English
Published: SpringerOpen 2024-01-01
Series:EJNMMI Physics
Subjects:
PET/CT
Deep progressive learning
Image quality
Sub-centimeter lesions quantification
Online Access:https://doi.org/10.1186/s40658-023-00607-x

Internet

https://doi.org/10.1186/s40658-023-00607-x

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