Introduction: Hydronephrosis is one of the major causes of referring infants for nuclear medicine investigation. Renal dynamic study is the most reliable investigation for such children. However direct evaluation of renogram leads to generation of parameters that have no physiological interpretation. The configuration of renogram is very much dependent upon the rate at which radiopharmace...

[1] We have completed the first global spatial deconvolution analysis of planetary gamma-ray data for lunar Th abundances as measured by the Lunar Prospector Gamma-ray Spectrometer. We tested two different spatial deconvolution techniques – Jansson’s method and the Pixon method – and determined that the Pixon method provides superior performance. The final deconvolved map results in a spatial r...

Diffusion tensor imaging (DTI) MRI is a noninvasive imaging method of the cerebral tissues whose fibers directions are not evaluated correctly in the regions of the crossing fibers. For the same reason the high angular resolution diffusion images (HARDI) are used for estimation of the fiber direction in each voxel. One of the main methods to specify the direction of fibers is usage of the spher...

The subject of this paper is beam deconvolution in small angular scale CMB experiments. The beam effect is reversed using the Jacobi iterative method, which was designed to solved systems of algebraic linear equations. The beam is a non circular one which moves according to the observational strategy. A certain realistic level of Gaussian instrumental noise is assumed. The method applies to sma...

The quantification of perfusion using dynamic susceptibility contrast MRI (DSC-MRI) requires deconvolution to obtain the residual impulse response function (IRF). In this work, a method using the Gaussian process for deconvolution (GPD) is proposed. The fact that the IRF is smooth is incorporated as a constraint in the method. The GPD method, which automatically estimates the noise level in eac...

This report studies an abstract approach to modeling the motion of large eddies in a turbulent flow. If the Navier-Stokes equations (NSE) are averaged with a local, spatial convolution type filter, φ = gδ ∗ φ, the resulting system is not closed due to the filtered nonlinear term uu. An approximate deconvolution operator D is a bounded linear operator which is an approximate filter inverse D(u) ...

Deconvolution interferometry successfully recovers the impulse response between two receivers without the need for an independent estimate of the source function. Here we extend the method of interferometry by deconvolution to multicomponent data in elastic media.As in the acoustic case, elastic deconvolution interferometry retrieves only causal scattered waves that propagate between two receiv...

Introduction With the advances in fast MR imaging techniques, it is possible to monitor the traversal of a MR contrast agent within tissues at short time intervals (of the order of a few seconds or less), thereby allowing the possibility to study blood flow at the tissue level. Dynamic contrastenhanced MRI (DCE MRI) is emerging as a promising approach for in vivo assessment of tissue microcircu...

while working on the problem of enemy missile fire prediction at MIT during World War II, Norbert Wiener developed a statistical process which separated radar signals from noise. The process was originally known as smoothing or Wiener prediction filtering. The inverse process of unsmoothing, or prediction error filtering, was called decomposition and was later termed deconvolution. Today, predi...

Fluorescence microscopy methods are an important imaging technique in cell biology. Due to their depth sensitivity they allow a direct 3-D imaging. However, the resulting volume data sets are undersampled in depth, and the 2-D slices are blurred and noisy. Reconstructing the full 3-D information from these data is therefore a challenging task, and of high relevance for biological applications. ...