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European Journal of Nuclear Medicine and Molecular Imaging

Erschienen in:

22.04.2022 | Review Article

Applications of Generative Adversarial Networks (GANs) in Positron Emission Tomography (PET) imaging: A review

verfasst von: Ioannis D. Apostolopoulos, Nikolaos D. Papathanasiou, Dimitris J. Apostolopoulos, George S. Panayiotakis

Erschienen in: European Journal of Nuclear Medicine and Molecular Imaging | Ausgabe 11/2022

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Abstract

Purpose

This paper reviews recent applications of Generative Adversarial Networks (GANs) in Positron Emission Tomography (PET) imaging. Recent advances in Deep Learning (DL) and GANs catalysed the research of their applications in medical imaging modalities. As a result, several unique GAN topologies have emerged and been assessed in an experimental environment over the last two years.

Methods

The present work extensively describes GAN architectures and their applications in PET imaging. The identification of relevant publications was performed via approved publication indexing websites and repositories. Web of Science, Scopus, and Google Scholar were the major sources of information.

Results

The research identified a hundred articles that address PET imaging applications such as attenuation correction, de-noising, scatter correction, removal of artefacts, image fusion, high-dose image estimation, super-resolution, segmentation, and cross-modality synthesis. These applications are presented and accompanied by the corresponding research works.

Conclusion

GANs are rapidly employed in PET imaging tasks. However, specific limitations must be eliminated to reach their full potential and gain the medical community's trust in everyday clinical practice.

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Titel: Applications of Generative Adversarial Networks (GANs) in Positron Emission Tomography (PET) imaging: A review
verfasst von: Ioannis D. Apostolopoulos
Nikolaos D. Papathanasiou
Dimitris J. Apostolopoulos
George S. Panayiotakis
Publikationsdatum: 22.04.2022
Verlag: Springer Berlin Heidelberg
Erschienen in: European Journal of Nuclear Medicine and Molecular Imaging / Ausgabe 11/2022
Print ISSN: 1619-7070
Elektronische ISSN: 1619-7089
DOI: https://doi.org/10.1007/s00259-022-05805-w

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Applications of Generative Adversarial Networks (GANs) in Positron Emission Tomography (PET) imaging: A review

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