Editorial: Recent advances in artificial intelligence-empowered ultrasound tissue characterization for disease diagnosis, intervention guidance, and therapy monitoring

Zhuhuang Zhou; Ke Lv; Po-Hsiang Tsui

doi:10.3389/fphys.2023.1234611

Editorial: Recent advances in artificial intelligence-empowered ultrasound tissue characterization for disease diagnosis, intervention guidance, and therapy monitoring

Front Physiol. 2023 Jun 28:14:1234611. doi: 10.3389/fphys.2023.1234611. eCollection 2023.

Authors

Zhuhuang Zhou¹, Ke Lv², Po-Hsiang Tsui^{3

4

5}

Affiliations

¹ Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing, China.
² Department of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
³ Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan.
⁴ Institute for Radiological Research, Chang Gung University, Taoyuan, Taiwan.
⁵ Division of Pediatric Gastroenterology, Department of Pediatrics, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan.

No abstract available

Keywords: artificial intelligence; deep learning; machine learning; ultrasound imaging; ultrasound tissue characterization.

Publication types

Editorial

Grants and funding

This work was supported in part by National Natural Science Foundation of China (No. 82171968), National Natural Science Foundation of China (No. 81873902), the Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences (No. 2020-I2M-C&T-B-039), National High Level Hospital Clinical Research Funding (No. 2022-PUMCH-B-065), National High Level Hospital Clinical Research Funding (No. 2022-PUMCH-D-001), and Beijing Natural Science Foundation (Grant No. 4222001).