The goal of this work is to recover transient dynamics in 3D dynamic MRI by reconstructing images with near-millimeter spatial resolution and sub-second temporal resolution without gating. This setting poses two major challenges: extreme undersampling and extreme computational/memory cost. To achieve this “extreme MRI”, we propose two innovations: explicit multi-scale low rank matrix factorization to regularize the problem and reduce memory usage, and stochastic optimization to reduce computation. We demonstrate the feasibility of the proposed method in DCE imaging acquired with 3D cones trajectory and lung imaging acquired with 3D UTE radial trajectory.
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