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[EditBox] Matlab_code_Q-VMP DL : 0: Compressive sensing is the reconstruction of sparse images or signals very few samples, by means of solving a tractable optimization problem. In the context of MRI, this can allow reconstruction many fewer k-space samples, thereby reducing scanning time. Previous work has shown that nonconvex optimization reduces still further the number of samples required for reconstruction, while still being tractable. In this work, we extend recent Fourier-based algorithms for convex optimization to the nonconvex setting, and obtain methods that combine the reconstruction abilities of previous nonconvex approaches with the computational speed of state-of-the-art convex methods. -Compressive sensing is the reconstruction of sparse images or signals very few samples, by means of solving a tractable optimization problem. In the context of MRI, this can allow reconstruction many fewer k-space samples, thereby reducing scanning time. Previous work has shown that nonconvex optimization reduces still further the number of samples required for reconstruction, while still being tractable. In this work, we extend recent Fourier-based algorithms for convex optimization to the nonconvex setting, and obtain methods that combine the reconstruction abilities of previous nonconvex approaches with the computational speed of state-of-the-art convex methods.
Date : 2025-12-31 Size : 17kb User : DDDJDDKDK