We present a method for the estimation of various features of the tissue micro-architecture using the diffusion magnetic resonance imaging. The considered features are designed from the displacement probability density function (PDF). The estimation is based on two steps: first the approximation of the signal by a series expansion made of Gaussian-Laguerre and Spherical Harmonics functions; fol...

This paper presents an analysis on the capacity and performance of MIMO-OFDM systems. The work is focused on the capacity of MIMO-OFDM systems over rician fading channel, in the case of the channel being known at the receiver only, which is more practical case of the channel. Simple expression for capacity is derived for the case of correlated rician fading. The performance of some MIMO-OFDM im...

The objective of this paper is to do the estimation of the noise in the Magnetic Resonance images and evaluate the noise reduction algorithm present in this paper. We propose a method for reduction of Rician noise in MRI. This method shows an optimal estimation result that is more accurate in recovering the true signal from Rician noise. The method proposed specifically for Rician noise reducti...

An assessment of spectrum efficiency for a microcellular land mobile radio system is presented by considering the desired signal as (fast) Rician fading with (slow) lognormal shadowing and co-channel interfering signals as uncorrelated (fast) Rayleigh fading superimposed over (slow) lognormal shadowing. Spectrum efficiency is defined in terms of reuse distance, Le., cluster size, traffic intens...

It is well known that magnetic resonance magnitude image data obey a Rician distribution. Unlike additive Gaussian noise, Rician "noise" is signal-dependent, and separating signal from noise is a difficult task. Rician noise is especially problematic in low signal-to-noise ratio (SNR) regimes where it not only causes random fluctuations, but also introduces a signal-dependent bias to the data t...

We present a novel statistical model, the generalized-Gaussian-Rician (GG-Rician) distribution, for characterization of synthetic aperture radar (SAR) images. Since accurate models lead to better results in applications such as target tracking, classification, or despeckling, characterizing SAR images various scenes including urban, sea surface, agricultural is essential. The proposed model bas...

conclusions in the case of existence gaussian noise, the results confirm that denoising is not effective on the measurement of t2* value. in the case of image distortion by rician noise, a predictor model is proposed to estimate the original t2* value. the predictor model is used to estimate the t2* value of new patients. the predicted t2* values were in good agreement with the corresponding or...

It is well-known that data from diffusion weighted imaging (DWI) follow the Rician distribution. The Rician distribution is also relevant for functional magnetic resonance imaging (fMRI) data obtained at high temporal or spatial resolution. We propose a general regression model for non-central χ (NC-χ) distributed data, with the heteroscedastic Rician regression model as a prominent special cas...