放射治疗
深度学习
工作流程
人工智能
计算机科学
癌症治疗
癌症
医学物理学
机器学习
医学
外科
数据库
内科学
作者
Xiaobo Wen,Chao Zhao,Bin Zhao,Miaomiao Yuan,Jee Suk Chang,Wei Liu,Jiaqi Meng,Lei Shi,Shuo Yang,Jing Zeng,Yi Yang
标识
DOI:10.1016/j.canrad.2023.07.015
摘要
In recent years, with the development of artificial intelligence, deep learning has been gradually applied to clinical treatment and research. It has also found its way into the applications in radiotherapy, a crucial method for cancer treatment. This study summarizes the commonly used and latest deep learning algorithms (including transformer, and diffusion models), introduces the workflow of different radiotherapy, and illustrates the application of different algorithms in different radiotherapy modules, as well as the defects and challenges of deep learning in the field of radiotherapy, so as to provide some help for the development of automatic radiotherapy for cancer.
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