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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

Year: 2026

Type: article

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.

Source: Quantitative Imaging in Medicine and Surgery

DOI: 10.21037/qims-2025-1757

Authors: Ling Wang, Shixiang Zhang, Sen Yang, Rongzheng Ma, Honglei Li, Jie Liu, Jin Gao, Yidan Wei, Liping Fu

Institutions: China-Japan Friendship Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College

Language: English

Topic: Medical Imaging Techniques and Applications

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: diamond

OpenAlex ID: W7125977656

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