Artificial Intelligence-Guided PET Image Reconstruction and Multi-Tracer Imaging: Novel Methods, Challenges, and Opportunities.

DOI
Publisher DOI
PubMed ID
40858423
Abstract
This article reviews recent advancements in PET/computed tomography imaging, emphasizing the transformative impact of total-body and long-axial field-of-view scanners, which offer increased sensitivity, larger coverage, and faster, lower-dose imaging. It highlights the growing role of artificial intelligence (AI) in enhancing image reconstruction, resolution, and multi-tracer applications, enabling rapid processing and improved quantification. AI-driven techniques, such as super-resolution, positron range correction, and motion compensation, are improving lesion detectability and image quality. The review underscores the potential of these innovations to revolutionize clinical and research PET imaging, while also noting the challenges in validation and implementation for routine practice.
Date Issued
2025-10
Publication Type
Article
Subject(s)
Subjects
Artificial intelligence
•
Image enhancement
•
Long-axial field-of-view
•
Multiplexed imaging
Language(s)
en
Author(s)
Dassanayake, Movindu
Reader, Andrew
Cook, Gary J R
Rahmim, Arman
Yousefirizi, Fereshteh
Additional Credits
Journal
PET Clinics
Publisher
Elsevier
ISSN
1879-9809
1556-8598
Access(Rights)
restricted
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