Realization of high-end PET devices that assist conventional PET devices in improving image quality via diffusion modeling.

ABSTRACT:

Purpose

This study aimed to implement high-end positron emission tomography (PET) equipment to assist conventional PET equipment in improving image quality via a distribution learning-based diffusion model.

Methods

A diffusion model was first trained on a dataset of high-quality (HQ) images acquired by a high-end PET device (uEXPLORER scanner), and the quality of the conventional PET images was later improved on the basis of this trained model built on null-space constraints. Data from 180 patients were used in this study. Among them, 137 patients who underwent total-body PET/computed tomography scans via a uEXPLORER scanner at the Sun Yat-sen University Cancer Center were retrospectively enrolled. The datasets of 50 of these patients were used to train the diffusion model.

SUBMITTER: Zhang Q 

PROVIDER: S-EPMC11656007 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature