Amplitude Distribution Model Research Articles

Targets Detection Based on Multifractal Method

Mean sea clutter scattering coefficient model can reflect the relationship between the scattering coefficient of sea clutter and radar parameters and environmental factors, commonly used at sea clutter radar range forecasts. Sea clutter amplitude distribution model is essentially in the form of a probability density function to describe the magnitude of the statistical properties of sea clutter. In this paper, based on the sea surface target detection process uncertain information based on multiple objective study of fractal theory, simulation results show that our detection methods to get good results, you can improve the reliability and intelligence of detection.

Clutter Modeling and Characteristic Analysis for Airborne MIMO Radar

For the issue of MIMO airborne radar clutter modeling in different environment conditions, a clutter modeling method based on composite model is proposed. It builds different types of clutter model through the changes of model parameters. The clutter model consists of clutter amplitude distribution model, and clutter cell scattering model. After considering the error factors such as element error, channel error, clutter fluctuation, a clutter modeling method based on composite model under error conditions is proposed. Finally, the computer simulation is made about the amplitude, the back-scatter coefficient, error factors, the space-time MV spectrum and the characteristic spectrum of different types of clutter through changing the model parameters. The simulation results show that: In ideal conditions, the Clutter Spectrum has good space-time characteristic, but in error conditions, the clutter fluctuates tempestuously, and in different environment conditions the fluctuation degree is different.

Liver tissue characterization for each pixel in ultrasound image using multi-Rayleigh model

In our previous study, we proposed the multi-Rayleigh model as an amplitude distribution model of fibrotic liver, and succeeded in the quantitative evaluation of liver fibrosis in the region of interest. In this paper, to evaluate liver fibrosis more accurately, the amplitude of each pixel in a clinical echo image was converted to hypoechoic and fibrotic probabilities using the multi-Rayleigh model. Clinical echo images of liver fibrosis were analyzed and the relationship between these probabilities and the stage of liver fibrosis were discussed. We also showed that the information on fibrotic tissue can be extracted more accurately using the fibrotic probability than using the conventional method based on the constant false alarm rate (CFAR) processing. We conclude that the proposed method is valid for the quantitative diagnosis of liver fibrosis.

Experimental Evaluation of Quantitative Diagnosis Technique for Hepatic Fibrosis Using Ultrasonic Phantom

Since clinical diagnosis using ultrasonic B-mode images depends on the skill of the doctor, the realization of a quantitative diagnosis method using an ultrasound echo signal is highly required. We have been investigating a quantitative diagnosis technique, mainly for hepatic disease. In this paper, we present the basic experimental evaluation results on the accuracy of the proposed quantitative diagnosis technique for hepatic fibrosis by using a simple ultrasonic phantom. As a region of interest crossed on the boundary between two scatterer areas with different densities in a phantom, we can simulate the change of the echo amplitude distribution from normal tissue to fibrotic tissue in liver disease. The probability density function is well approximated by our fibrosis distribution model that is a mixture of normal and fibrotic tissue. The fibrosis parameters of the amplitude distribution model can be estimated relatively well at a mixture rate from 0.2 to 0.6. In the inversion processing, the standard deviation of the estimated fibrosis results at mixture ratios of less than 0.2 and larger than 0.6 are relatively large. Although the probability density is not large at high amplitude, the estimated variance ratio and mixture rate of the model are strongly affected by higher amplitude data.

Experimental Evaluation of Quantitative Diagnosis Technique for Hepatic Fibrosis Using Ultrasonic Phantom

Since clinical diagnosis using ultrasonic B-mode images depends on the skill of the doctor, the realization of a quantitative diagnosis method using an ultrasound echo signal is highly required. We have been investigating a quantitative diagnosis technique, mainly for hepatic disease. In this paper, we present the basic experimental evaluation results on the accuracy of the proposed quantitative diagnosis technique for hepatic fibrosis by using a simple ultrasonic phantom. As a region of interest crossed on the boundary between two scatterer areas with different densities in a phantom, we can simulate the change of the echo amplitude distribution from normal tissue to fibrotic tissue in liver disease. The probability density function is well approximated by our fibrosis distribution model that is a mixture of normal and fibrotic tissue. The fibrosis parameters of the amplitude distribution model can be estimated relatively well at a mixture rate from 0.2 to 0.6. In the inversion processing, the standard deviation of the estimated fibrosis results at mixture ratios of less than 0.2 and larger than 0.6 are relatively large. Although the probability density is not large at high amplitude, the estimated variance ratio and mixture rate of the model are strongly affected by higher amplitude data.

Reliability of damage mechanism localisation by acoustic emission on glass/epoxy composite material plate

This investigation focuses on the analysis of the Acoustic Emission (AE) wave propagation and velocity evolution in glass/epoxy composite materials according to the fibre orientation. In this work, several piezoelectric sensors were placed on a large composite laminate in the same direction in order to analyse by one measure, the velocity and wave attenuation over a large distance. Then, the measured velocity was compared with the theoretical values of velocity that have been identified by the theoretical model analysis. This last velocity was used during a three-point bending test to analyse the damage localisation on the plate according to the amplitude distribution model developed in the “Laboratory of Roberval at the University of Technology of Compiègne”. The results of the damage localisation on the specimens were compared to the visually observed damage (delaminating, cracks…) and were corrected on the basis of the amplitude correction. Finally, the error ratio of localisation without correction was quantified. The originality of this study was to use the AE results obtained on a large laboratory specimen in order to improve the AE testing on an industrial structure scale.

Stability of Quantitative Evaluation Method of Liver Fibrosis Using Amplitude Distribution Model of Fibrotic Liver

In the clinical diagnosis of liver fibrosis using ultrasound B-mode images, there are some differences between individual doctors' diagnosis results. Hence, the realization of a quantitative diagnosis method using ultrasonic echo signals is strongly required. The probability density function (PDF) of the echo signal envelope is an important factor for ultrasound tissue characterization (TC). To realize the quantitative diagnosis of the stage of liver fibrosis, we proposed an amplitude distribution model using two Rayleigh distributions. We have been studying the possibility of the quantitative estimation of liver fibrosis by using this model. In this paper, we present the evaluation results of liver fibrosis for clinical data using the amplitude distribution model. Then, we present the stability of the quantitative estimation method of liver fibrosis using the amplitude distribution model by a simulation, and compare the results using the simulation and clinical data. Stability evaluation has enabled the estimation of the progress of liver fibrosis considering statistical dispersion.

Quantitative Estimation Method for Liver Fibrosis Based on Combination of Rayleigh Distributions

Since the clinical diagnosis based on ultrasonic B-mode images is dependent on the skill of the doctor, the realization of a quantitative diagnostic method using ultrasound echo signals is highly required. We have been investigating the quantitative diagnostic technique mainly on hepatic diseases. In this paper, we present a new analysis method using echo signals for the quantitative estimation of liver fibrosis. To quantitatively determine the stage of liver fibrosis, we propose a model in which the probability density function of echo amplitude is expressed as a combination of two Rayleigh distributions. These two Rayleigh distributions correspond to the echo components from the normal and diseased tissues. In addition, using this amplitude distribution model of echo amplitude, we present the estimation method to obtain the amount of fibrous tissue and stage of fibrotic degeneration of the liver from moments about mean of the echo amplitude. Basic examination using clinical images suggest that the quantitative estimation of liver fibrosis based on a combination of Rayleigh distributions is valid.

3P-54 Stability of quantitative evaluation method of liver fibrosis using amplitude distribution model of fibrotic liver(Poster Session)

3P-54 Stability of quantitative evaluation method of liver fibrosis using amplitude distribution model of fibrotic liver(Poster Session)

Whistler‐Mode Waves Modify the High‐Energy Electron Slot Region and the Outer Radiation Belt

AbstractA quasi‐linear diffusion model of energetic electrons (≥50 keV) is established by using the amplitude distribution model of the whistler‐mode waves, the ambient electron (~eV) density distribution model and the IGRF10 magnetic field model in 1 < L < 7 region. The numerical results reveal that the variation of plasmapause location changes the ambient electron density and wave intensity at the different L shells under the different geomagnetic conditions, and the variations of ambient electron density and wave intensity finally change the energetic electron loss region controlled by whistler‐mode hiss and acceleration region controlled by whistlermode chorus. The variation of the energetic electron loss region is consistent with the variation of the slot region, and meanwhile the variation of the electron acceleration region is consistent with the variation of the outer radiation belt, suggesting that the energetic electron loss driven by hiss and acceleration driven by chorus play quite important roles in modifying the slot region and outer electron belt during the recovery phases of the different storms. During the recovery phase of a great storm, for electrons with certain energy, since their loss region controlled by hiss disappears, the inner radiation belt can connect with the outer radiation belt together completely.