A fully automated, expert-perceptive image quality assessment system for whole-body [18F]FDG PET/CT

A fully automated, expert-perceptive image quality assessment system for whole-body [18F]FDG PET/CT

Abstract Background The quality of clinical PET/CT images is critical for both accurate diagnosis and image-based research. However, current image quality assessment (IQA) methods predominantly rely on handcrafted features and region-specific analyses, thereby limiting automation in whole-body and m...

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Bibliographic Details
Main Authors: Cong Zhang, Xin Gao, Xuebin Zheng, Jun Xie, Gang Feng, Yunchao Bao, Pengchen Gu, Chuan He, Ruimin Wang, Jiahe Tian
Format: Article
Language:English
Published: SpringerOpen 2025-04-01
Series:EJNMMI Research
Subjects:
[18F]FDG
Image quality assessment
Positron emission tomography/Computed tomography
Whole-body
Deep learning
Online Access:https://doi.org/10.1186/s13550-025-01238-2
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https://doi.org/10.1186/s13550-025-01238-2

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