机构:[1]Radiotherapy Physics and Technology Center, Cancer Center, West China Hospital, Sichuan University, Chengdu, 610041, P.R. China.四川大学华西医院[2]Department of Radiation Oncology, Beaumont Health System, Royal Oak, MI, USA.[3]Department of Radiation Oncology and Physics, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.[4]Shandong Provincial Key Medical and Health Laboratory of Pediatric Cancer Precision Radiotherapy, Jinan, China.
This work is supported by the National Natural Science Foundation of China (No. 12405390) and the Science and Technology Department of Sichuan Province, China (24ZDYF1028).
语种:
外文
PubmedID:
中科院(CAS)分区:
出版当年[2024]版:
无
最新[2023]版:
大类|2 区医学
小类|2 区核医学3 区肿瘤学
第一作者:
第一作者机构:[1]Radiotherapy Physics and Technology Center, Cancer Center, West China Hospital, Sichuan University, Chengdu, 610041, P.R. China.
通讯作者:
推荐引用方式(GB/T 7714):
Zhang Xiangbin,Yan Di,Xiao Haonan,et al.Modeling of artificial intelligence-based respiratory motion prediction in MRI-guided radiotherapy: a review[J].Radiation Oncology (London, England).2024,19(1):140.doi:10.1186/s13014-024-02532-4.
APA:
Zhang Xiangbin,Yan Di,Xiao Haonan&Zhong Renming.(2024).Modeling of artificial intelligence-based respiratory motion prediction in MRI-guided radiotherapy: a review.Radiation Oncology (London, England),19,(1)
MLA:
Zhang Xiangbin,et al."Modeling of artificial intelligence-based respiratory motion prediction in MRI-guided radiotherapy: a review".Radiation Oncology (London, England) 19..1(2024):140