16 citations · 32 across the 4 of their papers we have counts for
4 papers
Frame forecasting in cine MRI using the PCA respiratory motion model: comparing recurrent neural networks trained online and transformers
Michel Pohl, Mitsuru Uesaka, Hiroyuki Takahashi +2
Respiratory motion complicates accurate irradiation of thoraco-abdominal tumors during radiotherapy, as treatment-system latency entails target-location uncertainties. This work ad…
Real-time respiratory motion forecasting with online learning of recurrent neural networks for accurate targeting in externally guided radiotherapy
Michel Pohl, Mitsuru Uesaka, Hiroyuki Takahashi +2
In lung radiotherapy, infrared cameras can track reflective objects on the chest to estimate tumor motion due to breathing, but treatment system latencies hinder radiation beam pre…
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
Michel Pohl, Mitsuru Uesaka, Kazuyuki Demachi +1
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 resp…
Prediction of the Position of External Markers Using a Recurrent Neural Network Trained With Unbiased Online Recurrent Optimization for Safe Lung Cancer Radiotherapy
Michel Pohl, Mitsuru Uesaka, Hiroyuki Takahashi +2
During lung radiotherapy, the position of infrared reflective objects on the chest can be recorded to estimate the tumor location. However, radiotherapy systems have a latency inhe…