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- W3135955764 endingPage "137" @default.
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- W3135955764 abstract "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 emission tomography (PET) imaging. To this end, the underlying limitations/challenges of these imaging modalities are briefly discussed followed by a description of AI-based solutions proposed to address these challenges. This review will focus on mainstream generic fields, including instrumentation, image acquisition/formation, image reconstruction and low-dose/fast scanning, quantitative imaging, image interpretation (computer-aided detection/diagnosis/prognosis), as well as internal radiation dosimetry. A brief description of deep learning algorithms and the fundamental architectures used for these applications is also provided. Finally, the challenges, opportunities, and barriers to full-scale validation and adoption of AI-based solutions for improvement of image quality and quantitative accuracy of PET and SPECT images in the clinic are discussed." @default.
- W3135955764 created "2021-03-29" @default.
- W3135955764 creator A5004193178 @default.
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- W3135955764 creator A5036836472 @default.
- W3135955764 creator A5039181443 @default.
- W3135955764 creator A5048817483 @default.
- W3135955764 date "2021-03-01" @default.
- W3135955764 modified "2023-10-16" @default.
- W3135955764 title "The promise of artificial intelligence and deep learning in PET and SPECT imaging" @default.
- W3135955764 cites W2054591022 @default.
- W3135955764 cites W2070281674 @default.
- W3135955764 cites W2112136242 @default.
- W3135955764 cites W2115563908 @default.
- W3135955764 cites W2145283323 @default.
- W3135955764 cites W2240012579 @default.
- W3135955764 cites W2267700533 @default.
- W3135955764 cites W2271152362 @default.
- W3135955764 cites W2301970509 @default.
- W3135955764 cites W2352595529 @default.
- W3135955764 cites W2385563966 @default.
- W3135955764 cites W2418786089 @default.
- W3135955764 cites W2513595145 @default.
- W3135955764 cites W2556131806 @default.
- W3135955764 cites W2592929672 @default.
- W3135955764 cites W2599462151 @default.
- W3135955764 cites W2599895745 @default.
- W3135955764 cites W2611467245 @default.
- W3135955764 cites W2729145866 @default.
- W3135955764 cites W2747985375 @default.
- W3135955764 cites W2754132686 @default.
- W3135955764 cites W2755563559 @default.
- W3135955764 cites W2765429622 @default.
- W3135955764 cites W2766810683 @default.
- W3135955764 cites W2767848063 @default.
- W3135955764 cites W2768342898 @default.
- W3135955764 cites W2768901570 @default.
- W3135955764 cites W2780065026 @default.
- W3135955764 cites W2788611845 @default.
- W3135955764 cites W2789532252 @default.
- W3135955764 cites W2789588857 @default.
- W3135955764 cites W2789642020 @default.
- W3135955764 cites W2791282053 @default.
- W3135955764 cites W2797624406 @default.
- W3135955764 cites W2798538010 @default.
- W3135955764 cites W2801435301 @default.
- W3135955764 cites W2802431269 @default.
- W3135955764 cites W2804411736 @default.
- W3135955764 cites W2804601065 @default.
- W3135955764 cites W2805773775 @default.
- W3135955764 cites W2808302424 @default.
- W3135955764 cites W2885906943 @default.
- W3135955764 cites W2888958117 @default.
- W3135955764 cites W2888970401 @default.
- W3135955764 cites W2894799553 @default.
- W3135955764 cites W2895292895 @default.
- W3135955764 cites W2899335103 @default.
- W3135955764 cites W2899604332 @default.
- W3135955764 cites W2899686891 @default.
- W3135955764 cites W2901245852 @default.
- W3135955764 cites W2901476991 @default.
- W3135955764 cites W2902972155 @default.
- W3135955764 cites W2907190488 @default.
- W3135955764 cites W2907463061 @default.
- W3135955764 cites W2911573353 @default.
- W3135955764 cites W2912886337 @default.
- W3135955764 cites W2914533527 @default.
- W3135955764 cites W2914909991 @default.
- W3135955764 cites W2916124550 @default.
- W3135955764 cites W2919115771 @default.
- W3135955764 cites W2921467067 @default.
- W3135955764 cites W2947716587 @default.
- W3135955764 cites W2948025379 @default.
- W3135955764 cites W2949076424 @default.
- W3135955764 cites W2951015805 @default.
- W3135955764 cites W2955015477 @default.
- W3135955764 cites W2956939729 @default.
- W3135955764 cites W2958150439 @default.
- W3135955764 cites W2958646971 @default.
- W3135955764 cites W2962793481 @default.
- W3135955764 cites W2963073614 @default.
- W3135955764 cites W2964171289 @default.
- W3135955764 cites W2965034829 @default.
- W3135955764 cites W2969226503 @default.
- W3135955764 cites W2970280802 @default.
- W3135955764 cites W2971563774 @default.
- W3135955764 cites W2971791246 @default.
- W3135955764 cites W2974585575 @default.
- W3135955764 cites W2974786312 @default.
- W3135955764 cites W2975354219 @default.
- W3135955764 cites W2975696535 @default.
- W3135955764 cites W2979892984 @default.
- W3135955764 cites W2979990501 @default.
- W3135955764 cites W2981126002 @default.
- W3135955764 cites W2984759084 @default.
- W3135955764 cites W2998208444 @default.
- W3135955764 cites W2998494322 @default.
- W3135955764 cites W2998852648 @default.