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.
How to access this content:
For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.
After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.
After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.
Keywords