Joint Bayesian Compressed Sensing with Prior Estimate

Keywords

absolute accelerated acceleration acquiring acquisition acquisitions among amount applied applying approximate asymmetric atlas avoids becomes brain characterized combination combining complex compressed computed consistent consists contrast contrasts controlling couple dataset datasets degree depicts derived desirable diagnostic directly distinction distribution division done early encoding error estimating exploits extend facilitates faster features find fixed formed framework full fully gradient gradients health help hence horizontal imposing improved index initialize institute inversion iterations iteratively joint jointly kept known late least likelihood makes matrix minimized modeled modulating multiplicative mutual noise normalized omit operator optimal overall package partial pattern penalty pixel pixels plots posterior preparations prior problem proton quality rage random reconstructed reconstruction recovery regularization representation retrospectively returned root routine rule sampled sampling scale scaled schemes sciences sensing serve significantly simplicity slice smallest software solution solving space sparse sparsity spatial square squares supply support taking technology theory type update utilize variance variation vary vector vertical weightings yielded yielding