Denoising in Parallel Imaging Via Structured Low-Rank Matrix Approximation

Keywords

able acceleration addition adjacent amplification applied applies approaches approximated approximation artifacts averaging better block blocks blurring bottom calibration central channel channels chosen closest coil coils completion computationally computer conditioning conjunction contrast convolution correlation create decomposition distorts effective efficiently electrical eliminating engineering equal equations exhibit exhibits exist expensive extracting fewer filters finite five fold form formed free generically ghost heart implemented improve impulse institute interpolate interpolation iterations iterative iteratively jointly kernel lung matrices matrix mitigated noise noisy norms nullity observations operator original parallel peak potter practice preprocessing previous previously processing properties property propose proven rank reconstruct reconstructed reconstruction reconstructs reduces regularization regularized represent represents respectively response rightmost robust samples sensitivities sequentially severe shared simple simulated since singular smooth space spatial stat step structured sufficient suppress system tech theory thresholding thresholds truncated twelve uniform uniformly variation written zero zoomed