Sparse Tikhonov-Regularized SENSE MRI Reconstruction

Keywords

accelerates accomplished achieve actual advantage aliasing allowable amplification amplified analytical applications approaches approximate approximated array artifacts become behavior benefits biomedical block burden channel coil coils complex complexity computation computational computationally compute computer conditioned conjugate consider considered considering consists controlling corner cost covariance curvature curve decomposition demanding denotes dense described diagonal direct domain efficient efficiently electrical element elements encoding engineering error especially estimation expected factorization fast finding folded folding form formulated framework full generate good grow head important inverse known limitation linear major math matrix modified modifying multiplication noise note observation optimal optimization original overcome parallel performance posed precisely prior prob probability problem propose proposed quality rather real receiver reconstructed reconstruction reduce reduced reduces reduction regularization regularized representation represents residual sampling school sense sensitivity shape significantly simple simplifying simulation singular solution solving sparse step steps structure summation system table takes traditional transposed triangular upper vector vectors version visible west whitened wise written