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...

depth estimation of the top of the bedrock in the sedimentary basins is the main goal in geomagnetic explorations. the depth estimation of this kind of anomalies can be done using different methods, in the cases where the bedrock is magnetized. in this article, we use the standard euler deconvolution method and its results to interpret the magnetic data from the reshm region in semnan province ...

Introduction: Renal dynamic study is a well-established and popular test in routine practice of nuclear medicine. The test is non-invasive, rapid and unique in evaluation of the kidney function. In despite of its clinical values, the parameters derived from renogram are physiologically meaningless. That is due to the fact that renogram is not the true kidney function. From mathematical po...

Seismic interferometry is a field of growing interest in exploration seismology. In this paper we provide the theoretical basis for performing interferometry by deconvolution. We argue that for general models, deconvolution interferometry gives only the causal scattering response between any two receivers, as opposed to cross-correlation which gives both causal and acausal scattering responses....

introduction: renal dynamic study is a well-established and popular test in routine practice of nuclear medicine. the test is non-invasive, rapid and unique in evaluation of the kidney function. in despite of its clinical values, the parameters derived from renogram are physiologically meaningless. that is due to the fact that renogram is not the true kidney function. from mathematical points o...

1 Analyzing General Properties of Network Deconvolution 3 1.1 Network deconvolution algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.2 Optimality analysis of network deconvolution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.3 Modeling assumptions and intuitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...

We present a new method for general multidimensional multichannel deconvolution with finite impulse response (FIR) convolution and deconvolution filters using Gröbner bases. Previous work formulates the problem of multichannel FIR deconvolution as the construction of a left inverse of the convolution matrix, which is solved by numerical linear algebra. However, this approach requires the prior ...

Having attractiveness in digital cameras, the digital image processing is getting more imperative nowadays. One of the most common problems facing with digital photography is noise and blurring that needs restoration. In this paper, we present a new method for image blind deconvolution [2]. The Proposed Method employs threshold based image restoration technique in blind image deconvolution. The...