Feasibility of shortening the 18F-FDG Patlak scan time in a high-sensitivity short-axial field-of-view positron emission tomography-computed tomography system for oncological studies using deep learning denoising algorithms

Quantitative Imaging in Medicine and Surgery 2026 Open access

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Authors: Ling Wang, Shixiang Zhang, Sen Yang, Rongzheng Ma, Honglei Li, Jie Liu, Jin Gao, Yidan Wei, Liping Fu
DOI: 10.21037/qims-2025-1757
Cited by: 0

Abstract

Background: F-FDG) Patlak imaging in a high-sensitivity short-axial positron emission tomography-computed tomography (PET/CT) scanner by comparing various Patlak protocols alongside the application of a deep learning-based denoising algorithm. Methods: values between the abbreviated protocols (protocols 2, 3, and 4) and the standard protocol (protocol 1) was performed. Results: images acquired with different protocols were visually equivalent. Conclusions: analysis for both scientific and clinical purposes.

Fields of Study & Subjects

Medical Imaging Techniques and Applications Image and Signal Denoising Methods Radiation Dose and Imaging

Publication details

Journal / source
Quantitative Imaging in Medicine and Surgery
Volume
16
Issue
2
Pages
108–108
Publication date
28 January 2026
Language
EN