PURPOSE Regularizing parallel magnetic resonance imaging (MRI) reconstruction significantly improves image quality but requires tuning parameter selection. We propose a Monte Carlo method for automatic parameter selection based on Stein's unbiased risk estimate that minimizes the multichannel k-space mean squared error (MSE). We automatically tune parameters for image reconstruction methods tha...

In this paper, new classes of lower bounds on the outage error probability and on the mean-square-error (MSE) in Bayesian parameter estimation are proposed. The minima of the h-outage error probability and the MSE are obtained by the generalized maximum a-posteriori probability and the minimum MSE (MMSE) estimators, respectively. However, computation of these estimators and their corresponding ...

Purpose: Regularizing parallel magnetic resonance imaging (MRI) reconstruction significantly improves image quality but requires tuning parameter selection. We propose a Monte Carlo method for automatic parameter selection based on Stein’s unbiased risk estimate that minimizes the multichannel k-space mean squared error (MSE). We automatically tune parameters for image reconstruction methods th...

Multiscale entropy (MSE) analysis provides information about complexity on various time scales. The aim of this study was to test whether MSE is able to detect autonomic dysregulation in young patients with diabetes mellitus (DM). We analyzed heart rate (HR) oscillations, systolic (SBP) and diastolic blood pressure (DBP) signals in 14 patients with DM type 1 and 14 age- and sex-matched healthy ...

Multi-surface environments (MSE) combine several surfaces in a variety of physical arrangements to form a seamless information space. Large surfaces, such as tabletops and wall-displays are often used as a shared space to coordinate efforts, and handheld devices, such as tablets and smartphones, are generally used as personal spaces supporting individual tasks. MSE have shown benefits for suppo...

Different predictors and their approximators in nonlinear prediction regression models are studied. The minimal value of the mean squared error (MSE) is derived. Some approximate formulae for the MSE of ordinary and weighted least squares predictors are given.

Diierent predictors and their approximators in nonlinear prediction regression models are studied. The minimal value of the mean squared error (MSE) is derived. Some approximate formulae for the MSE of ordinary and weighted least squares predictors are given.

Multi-user searchable encryption (MSE) allows a user to encrypt its files in such a way that these files can be searched by other users that have been authorized by the user. The most immediate application of MSE is to cloud storage, where it enables a user to securely outsource its files to an untrusted cloud storage provider without sacrificing the ability to share and search over it. Any pra...

Myoclonic status epilepticus (MSE) is defined as prolonged period of myoclonic jerks that are correlated with epileptiform discharges on EEG. We here describe clinical features and video-EEG records of six adult patients with MSE who did not have a prior diagnosis of epilepsy. In four out of six patients, MSE was precipitated by drugs. Two out of four patients had chronic renal disease and rece...