A review on medical imaging synthesis using deep learning and its clinical applications

• Type of Material: Article
• Authors: Tonghe Wang, Emory University; Yang Lei, Emory University; Yabo Fu, Emory University; Jacob F. Wynne, Emory University; Walter Curran Jr, Emory University; Tian Liu, Emory University; Xiaofeng Yang, Emory University
• Language: English
• Date: 2020-12-11
• Publisher: WILEY
• Publication Version: Final Published Version
• Copyright Statement: © 2020 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.
• License: Creative Commons Attribution 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1002/acm2.13121
• Title of Journal or Parent Work: JOURNAL OF APPLIED CLINICAL MEDICAL PHYSICS
• Volume: 22
• Issue: 1
• Start Page: 11
• End Page: 36
• Grant/Funding Information: This research was supported in part by the National Cancer Institute of the National Institutes of Health under Award Number R01CA215718 and Emory Winship Cancer Institute pilot grant.
• Keywords: MR-IMAGES; CT; radiation therapy; Science & Technology; ATTENUATION CORRECTION; PET; Radiology, Nuclear Medicine & Medical Imaging; CONE-BEAM CT; Life Sciences & Biomedicine; PSEUDO-CT; GENERATIVE ADVERSARIAL NETWORKS; image synthesis; deep learning; LOW-DOSE CT; COMPUTED-TOMOGRAPHY; ITERATIVE RECONSTRUCTION; CONVOLUTIONAL NEURAL-NETWORK; MRI; DUAL-ENERGY CT
• Research Categories: Biology, Radiation; Health Sciences, Radiology; Biology, Neuroscience

Abstract

This paper reviewed the deep learning-based studies for medical imaging synthesis and its clinical application. Specifically, we summarized the recent developments of deep learning-based methods in inter- and intra-modality image synthesis by listing and highlighting the proposed methods, study designs, and reported performances with related clinical applications on representative studies. The challenges among the reviewed studies were then summarized with discussion.