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[1]易伟松,刘文强,陆 东,等.高光谱成像结合化学计量学诊断胃癌组织[J].中国医学物理学杂志,2015,32(01):124.[doi:10.3969/j.issn.1005-202X.2015.01.028]
[2]宋威,赵迪,鹿红,等.胃癌术后调强放疗射野角度优化的剂量学[J].中国医学物理学杂志,2015,32(06):815.[doi:doi:10.3969/j.issn.1005-202X.2015.06.012]
[J].Chinese Journal of Medical Physics,2015,32(4):815.[doi:doi:10.3969/j.issn.1005-202X.2015.06.012]
[3]易伟松,钱辉跃,江厚敏.光纤和显微拉曼光谱结合化学计量学鉴别胃癌组织[J].中国医学物理学杂志,2016,33(2):134.[doi:10.3969/j.issn.1005-202X.2016.02.006]
[4]卢晓光,刘细友,郑言宏,等.胃癌术后不同IMRT布野方式对剂量分布的影响[J].中国医学物理学杂志,2016,33(7):664.[doi:10.3969/j.issn.1005-202X.2016.07.004]
[5]刘光波,刘志坤,闫慧娟,等.不同照射技术在全胃癌放疗中的剂量学比较与分析[J].中国医学物理学杂志,2016,33(11):1111.[doi:10.3969/j.issn.1005-202X.2016.11.006]
[J].Chinese Journal of Medical Physics,2016,33(4):1111.[doi:10.3969/j.issn.1005-202X.2016.11.006]
[6]蒋大振,刘晖,戴静,等. 胃癌调强放疗中多叶光栅3种状态的剂量学比较[J].中国医学物理学杂志,2019,36(2):166.[doi:DOI:10.3969/j.issn.1005-202X.2019.02.009]
JIANG Dazhen,LIU Hui,DAI Jing,et al. Dosimetric comparison among split-field, fixed-jaw and rotating multi-leaf collimator in the radiotherapy of gastric carcinoma[J].Chinese Journal of Medical Physics,2019,36(4):166.[doi:DOI:10.3969/j.issn.1005-202X.2019.02.009]
[7]胡志纲,刘勇强,任建,等.胃癌术后不同布野方案对调强放疗剂量分布的影响[J].中国医学物理学杂志,2019,36(12):1400.[doi:DOI:10.3969/j.issn.1005-202X.2019.12.007]
HU Zhigang,LIU Yongqiang,REN Jian,et al.Effects of different field arrangements on the dose distribution of postoperative intensity-modulated radiotherapy for gastric cancer[J].Chinese Journal of Medical Physics,2019,36(4):1400.[doi:DOI:10.3969/j.issn.1005-202X.2019.12.007]
[8]赵呈陆,方志军,高永彬,等.基于改进型V-net卷积神经网络的胃壁分割方法[J].中国医学物理学杂志,2021,38(10):1243.[doi:DOI:10.3969/j.issn.1005-202X.2021.10.011]
ZHAO Chenglu,FANG Zhijun,GAO Yongbin,et al.Gastric wall segmentation based on improved V-net convolutional neural network[J].Chinese Journal of Medical Physics,2021,38(4):1243.[doi:DOI:10.3969/j.issn.1005-202X.2021.10.011]
[9]张育,赵轶峰,苏卓彬,等.基于卷积神经网络的胃癌癌前病变图像分类方法[J].中国医学物理学杂志,2022,39(2):209.[doi:DOI:10.3969/j.issn.1005-202X.2022.02.014]
ZHANG Yu,ZHAO Yifeng,SU Zhuobin,et al.Image classification of gastric precancerous lesions based on convolutional neural network[J].Chinese Journal of Medical Physics,2022,39(4):209.[doi:DOI:10.3969/j.issn.1005-202X.2022.02.014]
[10]周意龙,卫子然,蔡清萍,等.基于卷积神经网络胃癌分割与T分期算法[J].中国医学物理学杂志,2022,39(2):215.[doi:DOI:10.3969/j.issn.1005-202X.2022.02.015]
ZHOU Yilong,WEI Ziran,CAI Qingping,et al.Gastric cancer segmentation and T staging algorithm based on convolutional neural network[J].Chinese Journal of Medical Physics,2022,39(4):215.[doi:DOI:10.3969/j.issn.1005-202X.2022.02.015]