基于深度学习方法的伪CT图像合成技术研究及在放疗中的应用进展

Hongfei Sun; Xinye Ni; Jianhua Yang

doi:10.3760/cma.j.issn.0254-5098.2021.03.012

基于深度学习方法的伪CT图像合成技术研究及在放疗中的应用进展

Hongfei Sun, Xinye Ni, Jianhua Yang

自动化学院

科研成果: 期刊稿件 › 文献综述 › 同行评审

1 引用（Scopus）

摘要

With the improvement of the complexity of medical image synthesis and the demand for the accuracy of clinical radiotherapy, deep learning algorithm plays an increasingly important role in pseudo CT image synthesis and analysis. This paper classifies and analyzes the pseudo CT image synthesis technology based on deep learning method in terms of the types of image modes, and describes the ongoing application in radiotherapy.

投稿的翻译标题	Research on pseudo CT image synthesis technology based on deep learning method and its application in radiotherapy
源语言	繁体中文
页（从-至）	222-228
页数	7
期刊	Chinese Journal of Radiological Medicine and Protection
卷	41
期	3
DOI	https://doi.org/10.3760/cma.j.issn.0254-5098.2021.03.012
出版状态	已出版 - 25 3月 2021

关键词

Deep learning
Image guided radiotherapy
Pseudo CT

访问文件

10.3760/cma.j.issn.0254-5098.2021.03.012

其它文件与链接

链接到 Scopus 的出版物

引用此

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abstract = "With the improvement of the complexity of medical image synthesis and the demand for the accuracy of clinical radiotherapy, deep learning algorithm plays an increasingly important role in pseudo CT image synthesis and analysis. This paper classifies and analyzes the pseudo CT image synthesis technology based on deep learning method in terms of the types of image modes, and describes the ongoing application in radiotherapy.",

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N2 - With the improvement of the complexity of medical image synthesis and the demand for the accuracy of clinical radiotherapy, deep learning algorithm plays an increasingly important role in pseudo CT image synthesis and analysis. This paper classifies and analyzes the pseudo CT image synthesis technology based on deep learning method in terms of the types of image modes, and describes the ongoing application in radiotherapy.

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