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Artificial intelligence for nuclear medicine in oncology

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Abstract

As in all other medical fields, artificial intelligence (AI) is increasingly being used in nuclear medicine for oncology. There are many articles that discuss AI from the viewpoint of nuclear medicine, but few focus on nuclear medicine from the viewpoint of AI. Nuclear medicine images are characterized by their low spatial resolution and high quantitativeness. It is noted that AI has been used since before the emergence of deep learning. AI can be divided into three categories by its purpose: (1) assisted interpretation, i.e., computer-aided detection (CADe) or computer-aided diagnosis (CADx). (2) Additional insight, i.e., AI provides information beyond the radiologist's eye, such as predicting genes and prognosis from images. It is also related to the field called radiomics/radiogenomics. (3) Augmented image, i.e., image generation tasks. To apply AI to practical use, harmonization between facilities and the possibility of black box explanations need to be resolved.

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Authors and Affiliations

  1. Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, Kita 15, Nishi 7, Kita-Ku, Sapporo, Hokkaido, 060-8638, Japan

    Kenji Hirata, Noriyuki Fujima & Kohsuke Kudo

  2. Department of Nuclear Medicine, Hokkaido University Hospital, Sapporo, Japan

    Kenji Hirata

  3. Division of Medical AI Education and Research, Hokkaido University Graduate School of Medicine, Sapporo, Japan

    Kenji Hirata & Kohsuke Kudo

  4. Faculty of Health Sciences, Hokkaido University, Sapporo, Japan

    Hiroyuki Sugimori

  5. Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Japan

    Noriyuki Fujima & Kohsuke Kudo

  6. Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA

    Takuya Toyonaga

  7. Global Center for Biomedical Science and Engineering, Hokkaido University Faculty of Medicine, Sapporo, Japan

    Kohsuke Kudo

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  1. Kenji Hirata
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Hirata, K., Sugimori, H., Fujima, N. et al. Artificial intelligence for nuclear medicine in oncology. Ann Nucl Med 36, 123–132 (2022). https://doi.org/10.1007/s12149-021-01693-6

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