Spatiotemporal correlation enhanced real-time 4d-cbct imaging using convolutional lstm networks

HIGHLIGHTS

• What: To capture the in the projections the authors propose to use the convolutional LSTM (ConvLSTM) network for coefficient estimation. To address the issues, the authors propose a combined model that contains 1) a convolutional LSTM (ConvLSTM) and 2) a principal component analysis (PCA) model with prior 4D-CT to map a single 2D measured projection to one phase of 4D-CBCT. To determine the optimal configuration, the authors conducted a series of ablation experiments focusing on the number of hidden layers and cell layers within the ConvLSTM network. In this work, the goal is to develop . . .
  

   

  

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