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Abstract #4096

Accelerating cardiac dynamic imaging with video prediction using deep predictive coding networks

Xue Feng1 and Craig H Meyer1

1Biomedical Engineering, University of Virginia, Charlottesville, VA, United States

Deep predictive coding networks based on stacked recurrent convolutional neural network have shown great success in video prediction since they can learn to recognize and analyze the motion patterns of each element from previous frames. In this study we adopted this model to predict future frames in cardiac cine images and used a k-space substitution method to improve the prediction accuracy. It showed promises in accelerating cardiac dynamic imaging.

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