| Literature DB >> 34191161 |
Hossein Arabi1, Habib Zaidi2,3,4,5.
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.Entities:
Keywords: Artificial intelligence; Deep learning; Molecular imaging; Quantitative imaging; Radiation therapy
Year: 2020 PMID: 34191161 DOI: 10.1186/s41824-020-00086-8
Source DB: PubMed Journal: Eur J Hybrid Imaging ISSN: 2510-3636