Estimation of Mean Noise Propagation in SENSE for Generation of Optimized Undersampling Patterns

Keywords

acceleration albeit almost amplification applications approximation array assessment assuming automatic automatically best block blue body certain channel coil coils combined comes computational computationally computed consistent correlation corresponds count covariance dataset datasets deformed delta demanding depends desired determined deviate diagonal direct disc discussed divided efficiently enables encoding enhancement entries equal equally especially evaluated evaluation even expense expensive expression flash freedom fully furthermore generated generation give head hermitian identical incoherent incoherently interference introduced invariant inversion iterative local look magnetization make materials matrix measure middle minimize noise norm normalized noted novel numerical object observation offer offering operation optimal optimized parallel pattern patterns peak phantom pixel pixels positive potentially practice profiles projection propagation properties proposed qualitative readout reconstructed reconstruction reduced regular residual retrospectively routine sample sampled sampling schemes sector selecting sense sensitivities several since slices smoothly space spine squared strength strongly sums system theory trace trajectory transform transformations trying understood useful validate variance varying vector