| 摘要 |
<p>In SENSitivity Encoding (SENSE), the reconstructed images are susceptible to amplified noise and/or artifacts ifthe underlying matrix inversion procedure is ill-conditioned. In this work, we propose to firstly apply the conventional SENSE algorithm to obtain an initial estimate. This initial estimate undergoes filtering to improve the signal-to-noise ratio. Then, it is fed back to the reconstruction as a reference image to estimate the amount of aliasing that may arise from regularization. We derive the optimal regularized solution that minimizes the weighted sum of artifact and noise power.</p> |
