2D PC-MRI Compressed sensing (CS) and deep learning (DL) reconstruction techniques may introduce a reconstruction induced phase bias, distinct from eddy current-induced background phase offsets, which may impact the accuracy of flow measurements if not corrected. Herein, we analyzed this reconstruction induced phase bias to determine the maximum acceleration factor that could be used with CS and DL reconstruction frameworks for 2D PC-MRI while minimizing errors in peak velocity and total flow within ±5%.
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