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Application of artificial intelligence in nuclear medicine and molecular imaging: a review of current status and future perspectives for clinical translation

Dimitris Visvikis, Philippe Lambin, Kim Beuschau Mauridsen, Roland Hustinx, Michael Laßmann, Christoph Rischpler, Kuangyu Shi, Jan Pruim

2022European Journal of Nuclear Medicine and Molecular Imaging85 citationsDOIOpen Access PDF

Abstract

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.

Topics & Concepts

Focus (optics)Field (mathematics)Clinical PracticeArtificial intelligenceTransferabilityMedical physicsPerspective (graphical)RadiomicsMedical imagingComputer scienceMedicineData scienceEngineering ethicsNuclear medicineMachine learningFamily medicinePhysicsEngineeringMathematicsPure mathematicsOpticsLogitRadiomics and Machine Learning in Medical ImagingAdvanced X-ray and CT ImagingMedical Imaging Techniques and Applications
Application of artificial intelligence in nuclear medicine and molecular imaging: a review of current status and future perspectives for clinical translation | Litcius