Objective The automation of brachytherapy is the direction of future development. This article retrospectively studied the application of deep learning in brachytherapy of cervical cancer and clarified the status quo of development. Method This survey reviewed the application of machine learning and deep learning in brachytherapy for cervical cancer in the past 10 years. The survey retrieved and reviewed electronic journal articles in scientific databases such as Google Scholar and IEEE. The three sets of keywords used 1) deep learning, brachytherapy, 2) machine learning, brachytherapy, 3) automation, brachytherapy. Results Through research on the application of deep learning in brachytherapy, it is found that the U-net model is basically based on convolutional neural networks or some attention mechanisms are added to it, and it is applied to brachytherapy of prostate or cervical cancer. The automatic segmentation and reconstruction of the mid-source applicator (interpolation needle), target area delineation, optimization in the treatment planning system and dose calculation have achieved good results, proving that deep learning can be applied to the clinical treatment of brachytherapy. Conclusion The research on the application of deep learning in brachytherapy confirmed that deep learning can effectively promote the development of brachytherapy.
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