In this study, we combine classical “partial separable” model with deep-learning framework “variational network” for accelerated reconstruction of real-time cardiac MR imaging. The proposed PS-VN architecture achieves comparable reconstruction accuracy with baseline algorithm and reduce computational time to around 10 seconds for the reconstruction of over 4 thousand dynamic frames.
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