In Magnetic Resonance Imaging system, acquiring fewer measurements is required to reduce scan time, but it leads the aliasing artifact. Compressed Sensing is exploited to reconstruct image from undersampled data without artifacts by solving the optimization problem. However, It has some difficulites in selecting regularization parameters and this abstract propose the way to select regularization parameters by evaluating image quality. The quality of reconstructed image from proposed method is much better than the image from manual parameters. This study also has potential to be helpful in fast MR imaging.
This abstract and the presentation materials are available to members only; a login is required.