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Abstract #4792

Radial-RIM: accelerated radial 4D MRI using the recurrent inference machine

Chaoping Zhang1, Matthan W.A. Caan2,3,4, Robin Navest1, Jonas Teuwen1,5,6, and Jan-Jakob Sonke1
1Netherlands Cancer Institute, Amsterdam, Netherlands, 2Amsterdam UMC location University of Amsterdam, Amsterdam, Netherlands, 3Amsterdam Neuroscience, Amsterdam, Netherlands, 4Oslo University Hospital, Oslo, Norway, 5University of Amsterdam, Amsterdam, Netherlands, 6Radboud University Medical Center, Nijmegen, Netherlands

Synopsis

Keywords: Image Reconstruction, Image Reconstruction, radial, radiotherapy, liver, lung, respiratory motion

To accelerate the acquisition and reconstruction of the respiratory correlated (4D) radial MRI for image guided radiotherapy guidance, we propose a 3D radial-RIM network by adapting the forward model for Cartesian k-space in the regular RIM to radial k-space. Experiments show that the radial-RIM reconstructs images with better quality than the XD-GRASP compressed sensing for 3-4 times accelerated 4D radial free-breathing lung/liver acquisitions, with reconstruction time per slice reduced from 2 minutes to 1.9 seconds. Signal correlation exploited by the radial-RIM over the extra motion-state dimension contributes substantially to the image quality.

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Keywords