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Dataset Information

Reducing pediatric total-body PET/CT imaging scan time with multimodal artificial intelligence technology.


ABSTRACT:

Objectives

This study aims to decrease the scan time and enhance image quality in pediatric total-body PET imaging by utilizing multimodal artificial intelligence techniques.

Methods

A total of 270 pediatric patients who underwent total-body PET/CT scans with a uEXPLORER at the Sun Yat-sen University Cancer Center were retrospectively enrolled. 18F-fluorodeoxyglucose (18F-FDG) was administered at a dose of 3.7 MBq/kg with an acquisition time of 600 s. Short-term scan PET images (acquired within 6, 15, 30, 60 and 150 s) were obtained by truncating the list-mode data. A three-dimensional (3D) neural network was developed with a residual network as the basic structure, fusing low-dose CT images as prior information, which were fed to the network at differe

SUBMITTER: Zhang Q 

PROVIDER: S-EPMC10761657 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature