Applications of artificial intelligence and deep learning in molecular imaging and radiotherapy

被引：0
作者：
Hossein Arabi
Habib Zaidi
机构：
[1] Geneva University Hospital,Division of Nuclear Medicine and Molecular Imaging
[2] Geneva University,Geneva University Neurocenter
[3] University Medical Center Groningen,Department of Nuclear Medicine and Molecular Imaging, University of Groningen
[4] University of Southern Denmark,Department of Nuclear Medicine
来源：
European Journal of Hybrid Imaging | / 4卷
关键词：
Molecular imaging; Radiation therapy; Artificial intelligence; Deep learning; Quantitative imaging;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
This brief review summarizes the major applications of artificial intelligence (AI), in particular deep learning approaches, in molecular imaging and radiation therapy research. To this end, the applications of artificial intelligence in five generic fields of molecular imaging and radiation therapy, including PET instrumentation design, PET image reconstruction quantification and segmentation, image denoising (low-dose imaging), radiation dosimetry and computer-aided diagnosis, and outcome prediction are discussed. This review sets out to cover briefly the fundamental concepts of AI and deep learning followed by a presentation of seminal achievements and the challenges facing their adoption in clinical setting.
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