Commissioning and clinical implementation of an Autoencoder based Classification-Regression model for VMAT patientspecific QA in a multi-institution scenario (vol 161, pg 230, 2021)

doi:10.1016/j.radonc.2021.08.003

	Commissioning and clinical implementation of an Autoencoder based Classification-Regression model for VMAT patientspecific QA in a multi-institution scenario (vol 161, pg 230, 2021)
	Yang, Ruijie 1; Yang, Xueying 2; Wang, Le 3,4,5; Li, Dingjie 6; Guo, Yuexin 7; Li, Ying 8; Guan, Yumin 9; Wu, Xiangyang 10; Xu, Shouping 11; Zhang, Shuming 1,12
刊名	RADIOTHERAPY AND ONCOLOGY
	2021-10-01
卷号	163 页码:119-119
ISSN号	0167-8140
DOI	10.1016/j.radonc.2021.08.003
通讯作者	Geng, Lisheng(lisheng.geng@buaa.edu.cn) ; Sui, Jing(jsui@bnu.edu.cn)
资助项目	National Key Research and Development Program of China[2021YFE0202500] ; National Natural Science Foundation of China[11735003] ; National Natural Science Foundation of China[11975041] ; National Natural Science Foundation of China[11961141004] ; National Natural Science Foundation of China[61773380] ; National Natural Science Foundation of China[82022035] ; National Natural Science Foundation of China[81071237] ; Beijing Municipal Commission of Science and Technology Collaborative Innovation Project[Z201100005620012] ; Beijing Municipal Commission of Science and Technology Collaborative Innovation Project[Z181100001518005] ; Beijing Natural Science Foundation[7202223] ; Capital's Funds for Health Improvement and Research[2020-2Z-40919] ; fundamental Research Funds for the Central Universities ; Key project of Henan Provincial Department of Education[20B320035] ; NIH/NCI P30 Cancer Center Support Grant[CA008748] ; China International Medical Foundation[HDRS2020030206]
WOS研究方向	Oncology ; Radiology, Nuclear Medicine & Medical Imaging
语种	英语
出版者	ELSEVIER IRELAND LTD
WOS记录号	WOS:000704345500016
资助机构	National Key Research and Development Program of China ; National Natural Science Foundation of China ; Beijing Municipal Commission of Science and Technology Collaborative Innovation Project ; Beijing Natural Science Foundation ; Capital's Funds for Health Improvement and Research ; fundamental Research Funds for the Central Universities ; Key project of Henan Provincial Department of Education ; NIH/NCI P30 Cancer Center Support Grant ; China International Medical Foundation
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/45780]
专题	自动化研究所_脑网络组研究中心
通讯作者	Geng, Lisheng; Sui, Jing
作者单位	1.Peking Univ Third Hosp, Dept Radiat Oncol, Beijing, Peoples R China 2.Beihang Univ, Sch Phys, 9 Nansan St,Shahe Higher Educ Pk, Beijing 102206, Peoples R China 3.Chinese Acad Sci, Brainnetome Ctr, Beijing, Peoples R China 4.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China 5.Univ Chinese Acad Sci, Chinese Acad Sci, Sch Artificial Intelligence, 95 Zhongguancun East Rd, Beijing 100190, Peoples R China 6.Henan Canc Hosp, Dept Radiat Therapy, Zhengzhou, Peoples R China 7.Zhengzhou Univ, Affiliated Hosp 1, Dept Radiat Oncol, Zhengzhou, Peoples R China 8.Chongqing Med Univ, Affiliated Hosp 1, Dept Oncol, Chongqing, Peoples R China 9.Yantai Yuhuangding Hosp, Dept Radiat Therapy, Yantai, Peoples R China 10.Shanxi Prov Canc Hosp, Dept Radiotherapy, Xian, Peoples R China
推荐引用方式 GB/T 7714	Yang, Ruijie,Yang, Xueying,Wang, Le,et al. Commissioning and clinical implementation of an Autoencoder based Classification-Regression model for VMAT patientspecific QA in a multi-institution scenario (vol 161, pg 230, 2021)[J]. RADIOTHERAPY AND ONCOLOGY,2021,163:119-119.
APA	Yang, Ruijie.,Yang, Xueying.,Wang, Le.,Li, Dingjie.,Guo, Yuexin.,...&Sui, Jing.(2021).Commissioning and clinical implementation of an Autoencoder based Classification-Regression model for VMAT patientspecific QA in a multi-institution scenario (vol 161, pg 230, 2021).RADIOTHERAPY AND ONCOLOGY,163,119-119.
MLA	Yang, Ruijie,et al."Commissioning and clinical implementation of an Autoencoder based Classification-Regression model for VMAT patientspecific QA in a multi-institution scenario (vol 161, pg 230, 2021)".RADIOTHERAPY AND ONCOLOGY 163(2021):119-119.