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Abstract #0331

Highly accelerated Cardiac CINE MRI using Neural Fields

Tabita Catalán1, Matías Courdurier1,2, Axel Osses1,3, René Botnar1,4,5, Francisco Sahli Costabal1,4, and Claudia Prieto1,4
1Millennium Nucleus For Applied Control And Inverse Problems, Santiago, Chile, 2Department of Mathematics, Pontificia Universidad Católica de Chile, Santiago, Chile, 3Department of Mathematical Engineering, Universidad de Chile, Santiago, Chile, 4School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile, 5Institute for Biological and Medical Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile

Synopsis

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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