New Deep Learning Algorithm for Cervical Cancer Radiotherapy Organ Delineation

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Development of deep reinforcement learning algorithm for organ delineation in cervical cancer radiotherapy
Integration of SAM and RL models to improve segmentation accuracy and decision-making
Utilization of PPO and GAE methods during training phase for model optimization
AccuContour DL algorithm model employed for training with focus on accuracy and stability
Quantitative evaluation metrics such as DSC, HD95, ASSD, and RAVD used for assessment
Statistical analysis performed using SPSS software

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New Deep Learning Algorithm for Cervical Cancer Radiotherapy Organ Delineation

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