机构：[1]Department of Radiation Therapy, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China,广东省中医院[2]Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, CA, China,[3]Department of oncology, The Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou, China,[4]School of Medical Information Engineering, Guangzhou University of Chinese Medicine, Guangzhou, China,深圳市中医院深圳医学信息中心[5]Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hongkong, China,[6]School of Biomedical Engineering, Southern Medical University, Guangzhou, China
出处：
ISSN：
语种：
外文
WOS：
PubmedID：
中科院(CAS)分区：
出版当年[2020]版：
大类|2 区医学
小类|2 区肿瘤学2 区核医学
最新[2025]版：
大类|1 区医学
小类|2 区肿瘤学2 区核医学
JCR分区：
出版当年[2019]版：
Q1ONCOLOGYQ1RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
最新[2023]版：
Q1ONCOLOGYQ1RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
第一作者机构：[1]Department of Radiation Therapy, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China,
推荐引用方式(GB/T 7714)：
Z. Dai,X. Liang,L. Zhu,et al.Deep Learning-Based Automatic Delineation of Target Volumes and Organs at Risk of Breast Cancer for On-Line Dosimetric Evaluation[J].INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS.2021,111(3):E109-E110.
APA：
Z. Dai,X. Liang,L. Zhu,J. Tan,B. Zhang...&X. Wang.(2021).Deep Learning-Based Automatic Delineation of Target Volumes and Organs at Risk of Breast Cancer for On-Line Dosimetric Evaluation.INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS,111,(3)
MLA：
Z. Dai,et al."Deep Learning-Based Automatic Delineation of Target Volumes and Organs at Risk of Breast Cancer for On-Line Dosimetric Evaluation".INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS 111..3(2021):E109-E110
医学