The promise of artificial intelligence and deep learning in PET and SPECT imaging

This review sets out to discuss the foremost applications of artificial intelligence (AI), particularly deep learning (DL) algorithms, in single-photon emission computed tomography (SPECT) and positron (PET) imaging. To this end, underlying limitations/challenges these imaging modalities are briefly discussed followed by a description AI-based solutions proposed address challenges. will focus on mainstream generic fields, including instrumentation, image acquisition/formation, reconstruction low-dose/fast scanning, quantitative imaging, interpretation (computer-aided detection/diagnosis/prognosis), as well internal radiation dosimetry. A brief algorithms fundamental architectures used for is also provided. Finally, challenges, opportunities, barriers full-scale validation adoption improvement quality accuracy PET SPECT images clinic discussed.