Prediction of the motion of chest internal points using a recurrent neural network trained with real-time recurrent learning for latency compensation in lung cancer radiotherapy. (arXiv:2207.05951v1 [eess.IV])

During the radiotherapy treatment of patients with lung cancer, the radiation
delivered to healthy tissue around the tumor needs to be minimized, which is
difficult because of respiratory motion and the latency of linear accelerator
systems. In the proposed study, we first use the Lucas-Kanade pyramidal optical
flow algorithm to perform deformable image registration of chest computed
tomography scan images of four patients with lung cancer. We then track three
internal points close to the lung tumor based on the …

arxiv cancer compensation learning lung cancer network neural network prediction real-time recurrent neural network time