Editorial
Copyright ©The Author(s) 2020. Published by Baishideng Publishing Group Inc. All rights reserved.
Artif Intell Med Imaging. Jun 28, 2020; 1(1): 1-5
Published online Jun 28, 2020. doi: 10.35711/aimi.v1.i1.1
Rising role of artificial intelligence in image reconstruction for biomedical imaging
Xue-Li Chen, Tian-Yu Yan, Nan Wang, Karen M von Deneen
Xue-Li Chen, Tian-Yu Yan, Nan Wang, Karen M von Deneen, Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi’an 710126, Shaanxi Province, China
Author contributions: Chen XL designed the overall outline of the manuscript; Yan TY and Wang N performed the literature review and summary; Chen XL contributed to the writing and editing of the manuscript; von Deneen KM polished the language of the paper.
Supported by The National Key R& D Program of China, No. 2018YFC0910600; the National Natural Science Foundation of China No. 81627807 and 11727813; Shaanxi Science Funds for Distinguished Young Scholars, No. 2020JC-27; the Fok Ying Tung Education Foundation, No. 161104; and Program for the Young Top-notch Talent of Shaanxi Province.
Conflict-of-interest statement: The authors declare that they have no conflicts of interest.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Corresponding author: Xue-Li Chen, PhD, Professor, Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, No. 266, Xinglong Section of Xifeng Road, Xi’an 710126, Shaanxi Province, China. xlchen@xidian.edu.cn
Received: May 7, 2020
Peer-review started: May 7, 2020
First decision: May 15, 2020
Revised: June 9, 2020
Accepted: June 17, 2020
Article in press: June 17, 2020
Published online: June 28, 2020
Processing time: 63 Days and 19.4 Hours
Abstract

In this editorial, we review recent progress on the applications of artificial intelligence (AI) in image reconstruction for biomedical imaging. Because it abandons prior information of traditional artificial design and adopts a completely data-driven mode to obtain deeper prior information via learning, AI technology plays an increasingly important role in biomedical image reconstruction. The combination of AI technology and the biomedical image reconstruction method has become a hotspot in the field. Favoring AI, the performance of biomedical image reconstruction has been improved in terms of accuracy, resolution, imaging speed, etc. We specifically focus on how to use AI technology to improve the performance of biomedical image reconstruction, and propose possible future directions in this field.

Keywords: Biomedical imaging; Image reconstruction; Artificial intelligence; Machine learning; Deep learning; Tomography

Core tip: Three-dimensional biomedical imaging plays an important role in biology and medicine. We review recent progress on the applications of artificial intelligence (AI) in image reconstruction for biomedical imaging. We specifically focus on how to use AI technology to improve the performance of biomedical image reconstruction and propose possible future directions in this field. We believe that, with further development, AI technology will play an increasingly important role in biomedical image reconstruction.