Guoping Shan, Shunfei Yu, Zhongjun Lai, Zhiqiang Xuan, Jie Zhang, Binbing Wang, Yun Ge
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A Review of Artificial Intelligence Application for Radiotherapy.
Background and purpose: Artificial intelligence (AI) is a technique which tries to think like humans and mimic human behaviors. It has been considered as an alternative in a lot of human-dependent steps in radiotherapy (RT), since the human participation is a principal uncertainty source in RT. The aim of this work is to provide a systematic summary of the current literature on AI application for RT, and to clarify its role for RT practice in terms of clinical views.
Materials and methods: A systematic literature search of PubMed and Google Scholar was performed to identify original articles involving the AI applications in RT from the inception to 2022. Studies were included if they reported original data and explored the clinical applications of AI in RT.
Results: The selected studies were categorized into three aspects of RT: organ and lesion segmentation, treatment planning and quality assurance. For each aspect, this review discussed how these AI tools could be involved in the RT protocol.
Conclusions: Our study revealed that AI was a potential alternative for the human-dependent steps in the complex process of RT.
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