A model is developed for performance analysis of a microcellular digital mobile radio system with Rayleigh-faded cochannel interference, Gaussian noise, and narrow-band impulsive noise (Middleton’s Class A noise) using the differential phase shift keying modulation (DPSK) technique. The desired signal has been assumed to be Rician faded. The effects of selection diversity on the performance hav...

Magnetic Resonance Imaging (MRI) images are frequently corrupted by Rician noise during image gaining or transmission, which makes them worse than original. With the object to remove noise and lessen the loss of details as low as possible at the same time, we proposed a novel image denoising algorithm based on Genetic Algorithm (GA), Partial Differential Equations (PDE) and Total Variation (TV)...

Neural networks are a computational paradigm model of the human brain that has become popular in recent years. We have tried to address the problem of Glioma by creating a more accurate classifier which can act as an expert assistant to medical practitioners. Brain stem gliomas are now recognized as a heterogenous group of tumors. In this study proposed a prediction of Glioma in MR images using...

In order to accelerate the acquisition process in multiple-coil Magnetic Resonance scanners, parallel techniques were developed. These techniques reduce the acquisition time via a sub-sampling of the k -space and a reconstruction process. From a signal and noise perspective, the use of a acceleration techniques modify the structure of the noise within the image. In the most common algorithms, l...

Neural networks are a computational paradigm model of the human brain that has become popular in recent years. We have tried to address the problem of Gliomaby creating a more accurate classifier which can act as an expert assistant to medical practitioners. Brain stem gliomas are now recognized as a heterogenous group of tumors. In this paper, proposed a prediction of Glioma in MR images using...

We address the problem of robust estimation of tissue microstructure from Diffusion Magnetic Resonance Imaging (dMRI). On one hand, recent hardware improvements enable the acquisition of more detailed images, on the other hand, this comes along with a low Signal to Noise (SNR) ratio. In such a context, the approximation of the Rician acquisition noise as Gaussian is not accurate. We propose to ...

Least Squares (LS) and its minimum variance counterpart, Weighted Least Squares (WLS), have become very popular when estimating the Diffusion Tensor (DT), to the point that they are the standard in most of the existing software for diffusion MRI. They are based on the linearization of the Stejskal-Tanner equation by means of the logarithmic compression of the diffusion signal. Due to the Rician...

This paper analyzes the distribution and density functions of the probability of error for Rayleigh and Rician fading channels with diversity. An expression for the signal-to-noise ratio is derived for an asynchronous CDMA (A-CDMA) system with diversity. The error probability distribution and density functions are derived and plotted for different mean energy-to-noise ratios.

Rician noise introduces a bias into MRI measurements that can have a significant impact on the shapes and orientations of tensors in diffusion tensor magnetic resonance images. This is less of a problem in structural MRI, because this bias is signal dependent and it does not seriously impair tissue identification or clinical diagnoses. However, diffusion imaging is used extensively for quantita...