Keywords: Image Reconstruction, HeartNeural fields cardiac MRI (NF-cMRI), a method for highly accelerated CINE reconstruction using deep learning, is proposed. NF-cMRI relies on an intensity network, based on neural fields with Fourier features to encode a continuous reconstruction. The network is trained with one undersampled radial k-space data set without the need of a fully-sampled reference image. Good image quality of the heart is achieved with 8 radial spokes/cardiac frame. Results are compared against GRASP. Future work will focus on reducing reconstruction time and evaluating the proposed approach in prospectively undersampled k-space data.
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