Literature DB >> 34537129

The Evolution of Image Reconstruction in PET: From Filtered Back-Projection to Artificial Intelligence.

Kuang Gong1, Kyungsang Kim1, Jianan Cui1, Dufan Wu1, Quanzheng Li2.   

Abstract

PET can provide functional images revealing physiologic processes in vivo. Although PET has many applications, there are still some limitations that compromise its precision: the absorption of photons in the body causes signal attenuation; the dead-time limit of system components leads to the loss of the count rate; the scattered and random events received by the detector introduce additional noise; the characteristics of the detector limit the spatial resolution; and the low signal-to-noise ratio caused by the scan-time limit (eg, dynamic scans) and dose concern. The early PET reconstruction methods are analytical approaches based on an idealized mathematical model.
Copyright © 2021 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Artificial intelligence; Deep neural network; Image reconstruction

Mesh:

Year:  2021        PMID: 34537129     DOI: 10.1016/j.cpet.2021.06.004

Source DB:  PubMed          Journal:  PET Clin        ISSN: 1556-8598


  2 in total

Review 1.  Artificial Intelligence in Lymphoma PET Imaging:: A Scoping Review (Current Trends and Future Directions).

Authors:  Navid Hasani; Sriram S Paravastu; Faraz Farhadi; Fereshteh Yousefirizi; Michael A Morris; Arman Rahmim; Mark Roschewski; Ronald M Summers; Babak Saboury
Journal:  PET Clin       Date:  2022-01

Review 2.  Advances in Preclinical PET.

Authors:  Stephen S Adler; Jurgen Seidel; Peter L Choyke
Journal:  Semin Nucl Med       Date:  2022-03-18       Impact factor: 4.802

  2 in total

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