This paper deals with a preprocessing technique of magnetic resonance angiography (MRA) images, applied before maximum-intensity-projection (MIP). The purpose was to recover small low-intensity vessels, visible in individual slices, but lost in MIP images that usually have higher background level than the individual slices. The authors have developed a nonlinear three-dimensional spatial filter...

We constructed protein arrays according to a titration design to estimate the assay sensitivities over varying concentrations of flu vaccine and human immunoglobulin G (IgG). After imaging, we considered the problem of appropriately distinguishing background noise from foreground signal. We applied the median filter smoothing technique and estimated the differences of the observed signal compar...

A recursive formulation of an exponential smoothing filter is developed, within the framework of a least square error approach with data uncertainties that increase exponentially with time. An efficient implementation into Java is presented. By analogy to the Kalman filter, an interpretation of the gain as a ratio of uncertainties leads to a measure of validity for the recursive exponential fil...

The median filter is a special case of nonlinear filter used for smoothing signals. Since the output of the median filter is always one of the input samples, it is conceivable that certain signals could pass through the median filter unaltered. These signals, invariant to further passes of the median filter, define the signature of a filter and are referred to as root signals. This represents t...

Voxel-based morphometry (VBM) has been used to analyze diffusion tensor MRI (DT-MRI) data in a number of studies. In VBM, following spatial normalization, data are smoothed to improve the validity of statistical inferences and to reduce inter-individual variation. However, the size of the smoothing filter used for VBM of DT-MRI data is highly variable across studies. For example, a literature r...

Estimation problems for linear time-invariant systems with noisy input and output are considered. The smoothing problem is a least norm problem. An efficient algorithm using a Riccati-type recursion is derived. The equivalence between the optimal filter and an appropriately modified Kalman filter is established. The optimal estimate of the input signal is derived from the optimal state estimate...