[1]申海洋,彭祥炜,王兴,等.一种基于肝分段和肝癌轮廓融合的放疗靶区数据库建立方法[J].中国医学物理学杂志,2022,39(10):1250-1254.[doi:DOI:10.3969/j.issn.1005-202X.2022.10.012]
 SHEN Haiyang,PENG Xiangwei,et al.A method for establishing radiotherapy target area database based on the fusion of liver segment and liver cancer contour[J].Chinese Journal of Medical Physics,2022,39(10):1250-1254.[doi:DOI:10.3969/j.issn.1005-202X.2022.10.012]
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一种基于肝分段和肝癌轮廓融合的放疗靶区数据库建立方法()
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《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

卷:
39卷
期数:
2022年第10期
页码:
1250-1254
栏目:
医学影像物理
出版日期:
2022-11-02

文章信息/Info

Title:
A method for establishing radiotherapy target area database based on the fusion of liver segment and liver cancer contour
文章编号:
1005-202X(2022)10-1250-05
作者:
申海洋12彭祥炜2王兴1李广欣1黎功1袁克虹2
1.北京清华长庚医院放疗科, 北京 102200; 2.清华大学深圳国际研究生院, 广东 深圳 518000
Author(s):
SHEN Haiyang1 2 PENG Xiangwei2 WANG Xing1 LI Guangxin1 LI Gong1 YUAN Kehong2
1. Department of Radiotherapy, Beijing Tsinghua Changgung Hospital, Beijing 102200, China 2. International Graduate School, Tsinghua University, Shenzhen 518000, China
关键词:
肝癌精准放疗肝段识别靶区勾画人工智能
Keywords:
Keywords: liver cancer precise radiotherapy liver segment recognition target segmentation artificial intelligence
分类号:
R318
DOI:
DOI:10.3969/j.issn.1005-202X.2022.10.012
文献标志码:
A
摘要:
提出一种基于肝分段和肝癌轮廓融合的放疗靶区数据库建立和全过程数据质量管理方法,为后续人工智能靶区勾画或评估当前手工勾画提供数据支持。从肝癌数据库中取出原始图像,分别对其做带有肝脏放疗靶区勾画和分区分段轮廓标注工作,并通过图像融合技术使肝癌的放射治疗精确到肝段,最后使用深度学习的方法训练Unet网络以得到精准肝分割的神经网络模型,以实现针对肝癌的精准放疗。
Abstract:
Abstract: A method for radiotherapy target database establishment and the whole process data quality management based on the fusion of liver segment and liver cancer contour is proposed to provide data support for subsequent artificial intelligence-based target segmentation or evaluation of current manual delineation. The original images are selected from the liver cancer database for target segmentation in liver radiotherapy and labeling the contour in sections and segments. Through image fusion technology, the radiotherapy of liver cancer can be accurate to the liver segment. Unet is trained with deep learning method to obtain the neural network model for accurate liver segmentation, so as to achieve precise radiotherapy for liver cancer.

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备注/Memo

备注/Memo:
【收稿日期】2022-04-19 【基金项目】广东省自然科学基金(2022A1515011120);清华大学精准医学科研计划(10001020111) 【作者简介】申海洋,硕士,研究方向:医院管理,E-mail: shen-hy19@mails.tsinghua.edu.cn 【通信作者】黎功,教授,研究方向:放射治疗,E-mail: dr_gongli@163.com
更新日期/Last Update: 2022-10-27