Ultrasonic RF Echo Research Articles

An Ultrasonic RF Acquisition System for Plant Stems Based on Labview Double Layer Multiple Triggering.

Ultrasound is widely used in medical and engineering inspections due to its non-destructive and easy-to-use characteristics. However, the complex internal structure of plant stems presents challenges for ultrasound testing. The density and thickness differences in various types of stems can cause different attenuation of ultrasonic signal propagation and the formation of different echo locations. To detect structural changes in plant stems, it is crucial to acquire complete ultrasonic echo RF signals. However, there is currently no dedicated ultrasonic RF detection equipment for plant stems, and some ultrasonic acquisition equipment has limited memory capacity that cannot store a complete echo signal. To address this problem, this paper proposes a double-layer multiple-timing trigger method, which can store multiple trigger sampling memories to meet the sampling needs of different plant stems with different ultrasonic echo locations. The method was tested in experiments and found to be effective in acquiring complete ultrasonic RF echo signals for plant stems. This approach has practical significance for the ultrasonic detection of plant stems.

Improvement of myocardial displacement estimation using subkernels for cross correlation between ultrasonic RF echoes

Speckle tracking is a useful diagnostic method for assessing the cardiac function from ultrasonic echoes. Some factors influence the performance of the conventional speckle tracking method. Deformation due to myocardial contraction and relaxation decreases the correlation between RF echoes. Also, if a strong echo, such as echoes from the epicardium, is included in a correlation kernel, the displacement estimated from the kernel becomes close to the displacement of the epicardium even when the myocardium in the middle of the heart wall is the target to be tracked. To overcome such a problem, in the present study, we proposed a two-step tracking method. In the first step, the displacement is coarsely estimated using a correlation kernel of size similar to that in conventional speckle tracking of (13.8°, 9.1 mm) in the lateral and axial directions. The kernel is divided into small subkernels (2.8°, 1.9 mm). By estimating the correlation coefficient with respect to each subkernel and averaging correlation coefficients obtained from all subkernels, the contribution of a peculiar strong echo included in one of the subkernels can be suppressed. In the second step, the residual displacement is finely estimated using a smaller kernel (13.8°, 3.6 mm). Using a smaller kernel, the influence of myocardial deformation can be suppressed, but there might be multiple regions that have echo patterns similar to that in the kernel, leading to tracking errors. Therefore, the search region in the second step is narrowed because the coarse displacement has already been estimated and compensated in the first step. In the present study, the proposed method was validated using a phantom made of urethane rubber, which was deformed by an actuator. The displacement of the phantom could be estimated with a lower error of 0.059 mm by the proposed method compared to the error in the conventional method of 0.097 mm. Furthermore, the proposed method was applied to in vivo measurement of the human heart. The myocardial displacement could be estimated successfully even when the epicardium was included in a correlation kernel. These results show that the proposed method provides a more accurate and robust estimation of the myocardial displacement.

Optimization of feature extraction for automated identification of heart wall regions in different cross sections

In most current methods of evaluating the cardiac function based on echocardiography, the heart wall in an ultrasonic image is currently identified manually by an operator. However, this task is very time-consuming and leads to inter- and intraobserver variability. To facilitate the analysis and eliminate operator dependence, automated identification of heart wall regions is essential. We previously proposed a method of automatic identification of heart wall regions using multiple features based on information of the amplitude and phase of the ultrasonic RF echo signal by pattern recognition. In the present study, we investigate a new method of segmenting an ultrasonic image into the heart wall, lumen, and external tissues (includes pericardium) by two-step pattern recognition. Also, parameters in the proposed classification method were examined for application to different cross sections, i.e., long-axis and short-axis views, by considering differences in the motion and echogenicity of the heart walls. Furthermore, moving target indicator (MTI) filtering to suppress echoes from clutters was improved to enhance the separability in the short-axis view.

3P5-9 Optimization of Feature Extraction from Ultrasonic RF Echoes for Identification of Heart Wall Regions(Poster Session)

3P5-9 Optimization of Feature Extraction from Ultrasonic RF Echoes for Identification of Heart Wall Regions(Poster Session)

Statistics of the envelope of ultrasonic backscatter from human trabecular bone

The paper describes the investigations intended to compare the results of experimental measurements of backscattering properties of the trabecular bone with the results of computer simulations. Ultrasonic RF echoes were collected using two bone scanners operating at 0.58 and 1.3 MHz. The simulations of the backscattered RF echoes were performed using the scattering model of the trabecular bone that consisted of cylindrical and spherical elements uniformly distributed in water-like medium. For each measured or simulated RF backscatter the statistical properties of the signal envelope were determined. Experimental results suggest deviations of the backscattering properties from the Rayleigh distribution. The results of simulation suggest that deviation from Rayleigh distribution depends on the variation of trabeculae diameters and the number of thin trabeculae. Experimentally determined deviations corresponded well to the deviations calculated from simulated echoes assuming trabeculae thickness variation equaled to the earlier published histomorphometric study results.

Estimation of Scatterer Diameter by Normalized Power Spectrum of High-Frequency Ultrasonic RF Echo for Assessment of Red Blood Cell Aggregation

Red blood cell (RBC) aggregation, as one of the determinants of blood viscosity, plays an important role in blood rheology, including the condition of blood. RBC aggregation is induced by the adhesion of RBCs when the electrostatic repulsion between RBCs weakens owing to increases in protein and saturated fatty acid levels in blood, excessive RBC aggregation leads to various circulatory diseases. This study was conducted to establish a noninvasive quantitative method for assessment of RBC aggregation. The power spectrum of ultrasonic RF echoes from nonaggregating RBCs, which shows the frequency property of scattering, exhibits Rayleigh behavior. On the other hand, ultrasonic RF echoes from aggregating RBCs contain the components of reflection, which have no frequency dependence. By dividing the measured power spectrum of echoes from RBCs in the lumen by that of echoes from a posterior wall of the vein in the dorsum manus, the attenuation property of the propagating medium and the frequency responses of transmitting and receiving transducers are removed from the former spectrum. RBC aggregation was assessed by the diameter of a scatterer, which was estimated by minimizing the square difference between the measured normalized power spectrum and the theoretical power spectrum. In this study, spherical scatterers with diameters of 5, 11, 15, and 30 µm were measured in basic experiments. The estimated scatterer diameters were close to the actual diameters. Furthermore, the transient change of the scatterer diameters were measured in an in vivo experiment with respect to a 24-year-old healthy male during the avascularization using a cuff. The estimated diameters (12–22 µm) of RBCs during avascularization were larger than the diameters (4–8 µm) at rest and after recirculation. These results show the possibility of the use of the proposed method for noninvasive assessment of RBC aggregation.

Estimation of the Elevational Distance between Image Planes by Analysis of Ultrasonic Echoes from Point Scatterers

There are two approaches to three-dimensional (3D) image reconstruction using a 1D array ultrasonic transducer: mechanical linear scanning and free-hand scanning. Mechanical scanning employs a motorized mechanism to translate the transducer linearly. However, the large size and weight of the scanning system sometimes make it inconvenient to use. In free-hand scanning, a sensor (e.g., electromagnetic or optical) is attached to the ultrasonic transducer to measure the position and orientation of the transducer. These techniques are sensitive to the usage environment. Recently, sensorless free-hand scanning techniques have been developed. Seabra et al. reported sensorless free-hand techniques for the carotid artery by monitoring the velocity of the ultrasound probe [J. C. R. Seabra, L. M. Pedro, and J. F. Ferandes: IEEE Trans. Biomed. Eng. 56 (2009) 1442]. This system achieved an accuracy of 2.5 mm [root mean square (RMS) error] of the location. To develop accurate sensorless measurement, we propose a novel method using the phase shift between ultrasonic RF echoes. In this study, we measured the transmit-receive directivity of a linear-array transducer using a silicone phantom and estimated the elevational distance between two 2D US images using the phase shift. An accuracy of 49.9 µm in RMS, which is less than that of the previous sensorless free-hand method, could be achieved by the proposed method.

Estimation of Scatterer Diameter by Normalized Power Spectrum of High-Frequency Ultrasonic RF Echo for Assessment of Red Blood Cell Aggregation

Estimation of Scatterer Diameter by Normalized Power Spectrum of High-Frequency Ultrasonic RF Echo for Assessment of Red Blood Cell Aggregation

1Pa-55 Removal of Displacement Caused by Arriving of Pressure Wave for Accurate Estimation of Surface Roughness of Arterial Wall Using Ultrasonic RF Echo(Poster Session)

1Pa-55 Removal of Displacement Caused by Arriving of Pressure Wave for Accurate Estimation of Surface Roughness of Arterial Wall Using Ultrasonic RF Echo(Poster Session)

超音波RF信号のコヒーレンスに基づく心臓壁領域同定

超音波RF信号のコヒーレンスに基づく心臓壁領域同定

Automated Segmentation of Heart Wall Using Coherence Among Ultrasonic RF Echoes

In conventional ultrasonic tomographic images, the heart wall cannot be distinguished from the cardiac lumen automatically on the basis of only the echogenicity. One of the biggest problems is that echogenicity, which corresponds to the amplitude of an RF echo, in the heart wall is as low as that in the lumen. In this study, ultrasonic RF echoes from the heart wall and lumen were analyzed in the frequency domain in order to distinguish the heart wall from the lumen automatically. Temporal changes in complex frequency spectra were evaluated using the magnitude-squared coherence function. The coherence function of RF signals scattered from the interventricular septum (IVS) was high. In contrast, the coherence function in the right ventricle (RV) and left ventricle (LV) was low because the scatterers (blood cells) slipped off from the focal area of the ultrasonic beam by blood flow. For automated identification of the heart wall using the coherence function, the optimal threshold T0( f) for the coherence function should be determined. In this study, on the basis of the Bayes decision rule, the optimum value of T0( f) was determined. The coherence function of the region near the anterior wall in the RV was as high as that in the IVS because there are artifacts in the region near the anterior wall owing to echoes from the external tissue resulting from the sidelobe. However, the artifacts can be reduced by removing the stationary component from RF echoes before evaluating the coherence function. In vivo experimental results show that the differentiation of the heart wall from the lumen was improved significantly using the proposed method.

Breast tissue characterization using FARMA modeling of ultrasonic RF echo

A number of empirical and analytical studies demonstrated that the ultrasound RF echo reflected from tissue exhibits 1/ f characteristics. In this paper, we propose to model 1/ f characteristics of the ultrasonic RF echo by a novel parsimonious model, namely the fractional differencing auto regressive moving average (FARMA) process, and evaluated diagnostic value of model parameters for breast cancer malignancy differentiation. FARMA model captures the fractal and long term correlated nature of the backscattered speckle texture and facilitates robust efficient estimation of fractal parameters. In our study, in addition to the computer generated FARMA model parameters, we included patient age and radiologist’s prebiopsy level of suspicion (LOS) as potential indicators of malignant and benign masses. We evaluated the performance of the proposed set of features using various classifiers and training methods using 120 in vivo breast images. Our study shows that the area under the receiver operating characteristics (ROC) curve of FARMA model parameters alone is superior to the area under the ROC curve of the radiologist’s prebiopsy LOS. The area under the ROC curve of the three sets of features yields a value of 0.87, with a confidence interval of [0.85, 0.89], at a significance level of 0.05. Our results suggest that the proposed method of ultrasound RF echo model leads to parameters that can differentiate breast tumors with a relatively high precision. This set of RF echo features can be incorporated into a comprehensive computer-aided diagnostic system to aid physicians in breast cancer diagnosis. (E-mail: yazici@ecse.rpi.edu)

Quantitative Estimation of Diffused Liver Diseases Using Ultrasound Echo Signal

For the diagnosis of diffused liver diseases such as liver cirrhosis, a quantitative estimation method using ultrasound is required. In this paper, we present the quantitative estimation results of diffused liver diseases using ultrasonic RF echo signal of clinical data. The probability density function of echo amplitude from normal liver agrees well with the Rayleigh distribution. The probability density function of echo amplitude from cirrhotic liver is different from Rayleigh distribution. Using the statistical characteristics of echo amplitude, we propose quantitative indexes for the estimation of tissue structure. These indexes are applied to the clinical ultrasonic data. The RF echo data of 123 patients were used. Quantitative estimation results of diffused liver diseases using ultrasonic RF echo signal are closely related to fibrosis score of biopsy data. We conclude that the estimation using the statistical characteristics of echo amplitude is effective for the quantitative diagnosis of diffused liver diseases.