Applications of Generative Adversarial Networks (GANs) in Positron Emission Tomography (PET) imaging: A review.
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 topologi...
| Publicado en: | European Journal of Nuclear Medicine & Molecular Imaging Vol. 49; no. 11; pp. 3717 - 3740 |
|---|---|
| Autores principales: | , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Sep2022
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=158671648&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 158671648 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 16197070 NPC jtl: European Journal of Nuclear Medicine & Molecular Imaging issn: 16197070 maglogo: N pubinfo: dt: Sep2022 vid: 49 iid: 11 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 158671648 10.1007/s00259-022-05805-w 158671648 ppf: 3717 ppct: 23 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Applications of Generative Adversarial Networks (GANs) in Positron Emission Tomography (PET) imaging: A review. aug: au: Apostolopoulos, Ioannis D. Papathanasiou, Nikolaos D. Apostolopoulos, Dimitris J. Panayiotakis, George S. affil: Department of Medical Physics, School of Medicine, University of Patras, Patras, Greece sug: ab: 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. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|