Application of artificial intelligence in nuclear medicine and molecular imaging: a review of current status and future perspectives for clinical translation.
Artificial intelligence (AI) will change the face of nuclear medicine and molecular imaging as it will in everyday life. In this review, we focus on the potential applications of AI in the field, both from a physical (radiomics, underlying statistics, image reconstruction and data analysis) and a cl...
| Publicado en: | European Journal of Nuclear Medicine & Molecular Imaging Vol. 49; no. 13; pp. 4452 - 4464 |
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| Autores principales: | , , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Nov2022
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| 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=159866273&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 159866273 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: Nov2022 vid: 49 iid: 13 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 159866273 157866965 10.1007/s00259-022-05891-w 159866273 ppf: 4452 ppct: 12 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Application of artificial intelligence in nuclear medicine and molecular imaging: a review of current status and future perspectives for clinical translation. aug: au: Visvikis, Dimitris Lambin, Philippe Beuschau Mauridsen, Kim Hustinx, Roland Lassmann, Michael Rischpler, Christoph Shi, Kuangyu Pruim, Jan affil: LaTIM, INSERM, UMR 1101, University of Brest, Brest, France sug: ab: Artificial intelligence (AI) will change the face of nuclear medicine and molecular imaging as it will in everyday life. In this review, we focus on the potential applications of AI in the field, both from a physical (radiomics, underlying statistics, image reconstruction and data analysis) and a clinical (neurology, cardiology, oncology) perspective. Challenges for transferability from research to clinical practice are being discussed as is the concept of explainable AI. Finally, we focus on the fields where challenges should be set out to introduce AI in the field of nuclear medicine and molecular imaging in a reliable manner. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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