The application of deep learning (DL) artificial intelligence techniques within the realm of medical imaging, particularly in nuclear medicine, has emerged as a vibrant area of investigation in recent years. Single photon emission computed tomography (SPECT), a crucial branch of nuclear medicine imaging, furnishes clinicians with valuable functional information, distinctively contributing to diagnostic accuracy. This paper systematically reviews the principal research directions, significance, and current state-of-the-art applications of DL in SPECT, pinpointing existing limitations in current studies. Furthermore, it provides a forward-looking outlook on prospective avenues of inquiry in this rapidly evolving field.
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Seoul National University,Department of Health Science and Technology, Graduate School of Convergence Science and TechnologySeoul National University,Department of Health Science and Technology, Graduate School of Convergence Science and Technology
Kyounghyoun Kwon
Dongkyu Oh
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Seoul National University Bundang Hospital,Department of Nuclear MedicineSeoul National University,Department of Health Science and Technology, Graduate School of Convergence Science and Technology
Dongkyu Oh
Ji Hye Kim
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Seoul National University Bundang Hospital,Department of Nuclear MedicineSeoul National University,Department of Health Science and Technology, Graduate School of Convergence Science and Technology
Ji Hye Kim
Jihyung Yoo
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Seoul National University College of Medicine,Department of Nuclear MedicineSeoul National University,Department of Health Science and Technology, Graduate School of Convergence Science and Technology
Jihyung Yoo
Won Woo Lee
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Seoul National University Bundang Hospital,Department of Nuclear MedicineSeoul National University,Department of Health Science and Technology, Graduate School of Convergence Science and Technology