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

• Main Authors: Hossein Arabi, Habib Zaidi
• Format: Article
• Language: English
• Published: SpringerOpen 2020-09-01
• Series: European Journal of Hybrid Imaging
• Subjects: Molecular imaging; Radiation therapy; Artificial intelligence; Deep learning; Quantitative imaging
• Online Access: http://link.springer.com/article/10.1186/s41824-020-00086-8

Abstract 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.