Application of artificial intelligence in tumor radiotherapy
Objective To review the current status of artificial intelligence,represented by deep learning,in radiotherapy,and elaborate on the current problems and development prospects.Methods A literature search for the period from 2012 to 2023 was conducted in the PubMed and CNKI databases using the keywords"radiotherapy,artificial intelligence,deep learning,automatic contouring,quality assurance,and image registration".Inclusion criteria:(1)Application of artificial intelligence in radiotherapy image registration and automatic delineation;(2)The application of artificial intelligence in the formulation of radiotherapy plans;(3)The application of artificial intelligence in quality assurance and efficacy prediction of radiotherapy.Exclusion criteria:Literature with low relevance and credibility to radiation therapy.Finally,85 relevant articles were selected for analysis.Results Deep learning technologies within the realm of artificial intelligence have as-sumed a critical role across various stages of radiotherapy,particularly in the field of medical image processing.Current research demonstrates that deep learning can significantly reduce the workload of radiological physi-cians in the areas of image synthesis and registration,as well as in the automatic delineation of target areas,thereby en-hancing the consistency of the outcomes.However,the application of these technologies in the development of radiothera-py plans and in quality assurance still requires further refinement and clinical validation to fully realize their potential.Conclusions The combination of artificial intelligence and radiotherapy has made some initial achievements but still faces many challenges such as the quantity and quality of data,algorithm reliability,ethical and moral issues.Therefore,con-tinuous algorithm optimization is necessary for the application of artificial intelligence to clinical practice to accelerate the development of this field.