Use of two-dimensional phase-only filters and compounding for speckle reduction and edge detection in ultrasonic B-scan images.

Phase-only filters (POF) are studied for speckle reduction and edge detection in ultrasonic images. A methodology is developed for selecting the filters and compounding the filtered outputs. Studies on four speckled images show that the parametric images of compounded phases highlighted the boundaries. Estimating the heterogeneity index defined as the ratio of the arithmetic to the geometric mean of the magnitudes, the boundaries were also highlighted, providing a second means of detecting boundaries. This technique based on diversity created through a bank of POF reduces the speckle as well as highlights the boundaries of targetlike regions.

Speckle reduction in ultrasonic images through a maximum likelihood based adaptive filter.

Speckle poses serious problems in the interpretation of ultrasound images. It reduces contrast and resolution, making it difficult to identify the presence of abnormalities in B mode images. Using a recently proposed compound probability density function (pdf) for the statistics of the backscattered ultrasonic signals, an adaptive filter for speckle reduction is implemented and tested on B mode images of a tissue mimicking phantom. Results suggest that the adaptive filter based on a maximum likelihood approach improves the ability to classify targets in images while retaining the details in the original unprocessed image.

Comments on 'The effect of logarithmic compression on the estimation of the Nakagami parameter for ultrasonic tissue characterization'.

In a recently published paper (Tsui et al 2005 Phys. Med. Biol. 50 3235-44), the authors demonstrated estimation of the Nakagami parameter of the logcompressed envelopes and the application of such an approach in ultrasonic tissue characterization. The comments in this letter suggest that the authors ignored some important statistical properties of logcompressed data leading to serious errors in their studies and results.

Application of the compound probability density function for characterization of breast masses in ultrasound B scans.

The compound probability density function (pdf) is investigated for the ability of its parameters to classify masses in ultrasonic B scan breast images. Results of 198 images (29 malignant and 70 benign cases and two images per case) are reported and compared to the classification performance reported by us earlier in this journal. A new parameter, the speckle factor, calculated from the parameters of the compound pdf was explored to separate benign and malignant masses. The receiver operating characteristic curve for the parameter resulted in an A(z) value of 0.852. This parameter was combined with one of the parameters from our previous work, namely the ratio of the K distribution parameter at the site and away from the site. This combined parameter resulted in an A(z) value of 0.955. In conclusion, the parameters of the K distribution and the compound pdf may be useful in the classification of breast masses. These parameters can be calculated in an automated fashion. It should be possible to combine the results of the ultrasonic image analysis with those of traditional mammography, thereby increasing the accuracy of breast cancer diagnosis.

Computer aided classification of masses in ultrasonic mammography.

Frequency compounding was recently investigated for computer aided classification of masses in ultrasonic B-mode images as benign or malignant. The classification was performed using the normalized parameters of the Nakagami distribution at a single region of interest at the site of the mass. A combination of normalized Nakagami parameters from two different images of a mass was undertaken to improve the performance of classification. Receiver operating characteristic (ROC) analysis showed that such an approach resulted in an area of 0.83 under the ROC curve. The aim of the work described in this paper is to see whether a feature describing the characteristic of the boundary can be extracted and combined with the Nakagami parameter to further improve the performance of classification. The combination of the features has been performed using a weighted summation. Results indicate a 10% improvement in specificity at a sensitivity of 96% after combining the information at the site and at the boundary. Moreover, the technique requires minimal clinical intervention and has a performance that reaches that of the trained radiologist. It is hence suggested that this technique may be utilized in practice to characterize breast masses.

Use of non-Rayleigh statistics for the identification of tumors in ultrasonic B-scans of the breast.

A model for the scattering of ultrasound from breast tissue is proposed. The model is based on the use of non-Rayleigh statistics, specifically the K distribution to describe the backscattered echo from the tissue. A multiparameter test based on this model has been designed to characterize the tissue. The data from the B-scan images of the breasts of 6 different patients were analyzed using this model. The results indicate that the non-Rayleigh statistics seem to be useful in characterizing and identifying malignant, benign, and normal tissue regions.

A model for ultrasonic scattering from tissues based on the K distribution.

A model for the backscattered ultrasound echo from tissues is presented. The model takes into account the fact that the range cell being insonified may contain only a few scatterers and the number may not be large enough to justify the use of a Gaussian model which results in Rayleight statistics for the echo. Furthermore, the model also considers the case where the echogenicity of the scatterers in the range cell may not be uniform, the lack of uniformity resulting from variations in scattering cross-sections produced by the chemical as well as biochemical changes brought on by the presence of disease, growth of benign or malignant tumours, etc. The model is developed from the fundamental principles of scattering using the results available in radar. This new model results in a two-parameter distribution, namely the K distribution for the echo, thereby making it possible to gain information on the number as well as scattering cross-sections of the scatterers in the range cell. The model is extended to include the effects due to the presence of scatterers having some regular or periodic orientation in the range cell, resulting in the so-called generalized K distribution which approximates to Rayleight, Rician, or Gaussian under various limiting cases. Results of computer simulations and experiments on tissue-mimicking phantoms are also provided, which strongly suggest that this new model offers potential for tissue characterization.

The use of the compound probability density function in ultrasonic tissue characterization.

Recently, a compound probability density function (pdf) was proposed to model the envelope of the ultrasonic backscattered echo from tissues. This pdf will allow local and global variations in scattering cross sections and even multiple scattering in tissue. It approximates to the Nakagami, K or Rayleigh distributions under different limiting conditions, thus making it very versatile. In this work, a new parameter associated with compound pdf, speckle factor, has been introduced to characterize the scattering conditions. The usefulness of this parameter for tissue characterization has been explored through computer simulation of ultrasonic A scans and analyses of the data collected from tissue-mimicking phantoms. Results suggest the potential applications of the compound pdf and its parameters in ultrasonic tissue characterization.

Subharmonic generation from ultrasonic contrast agents.

Ultrasonic contrast agents are used to enhance backscatter from blood and thus aid in delineating blood from surrounding tissue. However, behaviour of contrast agents in an acoustic field is nonlinear and leads to harmonic components in the backscattered signal. Various research groups have investigated second-harmonic emissions. In this work, the subharmonic emission from contrast agents is investigated with a view towards potential use in imaging. It is shown that the microbubbles with various surface properties, such as contrast agents, generate significant subharmonics under various insonating conditions. Theoretical results as well as experimental results using Optison indicate the generation of strong subharmonics with burst insonation at twice the resonant frequency of the microbubble. It is suggested that subharmonic imaging may provide a better modality than second-harmonic imaging to delineate blood from tissue and will be of significant importance for imaging deep vessels, such as in echocardiography and vascular diseases, due to the high signal-to-clutter ratio of the subharmonic imaging.

Classification of breast masses in ultrasonic B scans using Nakagami and K distributions.

Classification of breast masses in greyscale ultrasound images is undertaken using a multiparameter approach. Five parameters reflecting the non-Rayleigh nature of the backscattered echo were used. These parameters, based mostly on the Nakagami and K distributions, were extracted from the envelope of the echoes at the site, boundary, spiculated region and shadow of the mass. They were combined to create a linear discriminant. The performance of this discriminant for the classification of breast masses was studied using a data set consisting of 70 benign and 29 malignant cases. The Az value for the discriminant was 0.96 +/- 0.02, showing great promise in the classification of masses into benign and malignant ones. The discriminant was combined with the level of suspicion values of the radiologist leading to an Az value of 0.97 +/- 0.014. The parameters used here can be calculated with minimal clinical intervention, so the method proposed here may therefore be easily implemented in an automated fashion. These results also support the recent reports suggesting that ultrasound may help as an adjunct to mammography in breast cancer diagnostics to enhance the classification of breast masses.

Statistical modeling of atherosclerotic plaque in carotid B mode images--a feasibility study.

A feasibility study undertaken to model atherosclerotic plaque in carotid B-mode images is presented. The study is based on 33 regions-of-interest collected from arterial images obtained from four patients. A bimodal gamma distribution with five parameters is proposed to model the statistics of the pixels in the gray-level images. The parameters of the distribution are evaluated for regions containing plaque using curve-fitting techniques. This bimodal distribution appears to be a reasonable fit to the statistics of the pixels. This statistical model may aid in the objective classification of arterial plaque through the use of its parameters.

Characterization of ultrasonic transducers using a fiberoptic sensor.

The PVDF (polyvinylidene fluoride) hydrophones, commonly used to measure the characteristics of ultrasonic transducers, suffer from a number of drawbacks. They disturb the field distribution to be measured and cause spatial averaging effects because of their finite aperture. In addition, they are very delicate and susceptible to damage. To overcome some of these problems, the authors previously proposed the use of an optical fiber-based probe to measure the ultrasonic fields. In this paper, this fiberoptic ultrasonic sensor is used to measure the characteristics of six transducers, focused as well as unfocused, covering a frequency range of 2.25 MHz to 20 MHz. Results obtained using the fiberoptic sensor are compared with those obtained using a calibrated PVDF needle hydrophone with an effective diameter of 0.5 mm. The temporal responses as well as the beam profiles of the transducers measured using the fiberoptic sensor show excellent agreement with the results obtained using the PVDF needle hydrophone.

Subharmonic signal generation from contrast agents in simulated neovessels.

Detection and measurement of blood flow in neovessels around a tumor can yield prognostic information about the tumor. Early detection and classification may help differentiate benign and malignant tumors; thus, improving patient management. This can be accomplished by injecting ultrasonic contrast agents and measuring the backscattered signals from them. Use of the subharmonic backscattered signals from these agents may be better than fundamental or second harmonic components because of the negligible subharmonics generated by the surrounding tissue. Preliminary results on the detection and measurement of subharmonic signal components up to 12 dB (at increasing pressures) from very small tubes (200 to 300 microm diameter) are reported, demonstrating the possibility and potential application of subharmonic imaging in detecting tumor angiogenesis.

Characterization of ultrasonic B-scans using non-Rayleigh statistics.

The envelope of the ultrasonic echo backscattered from tissues is modeled using non-Rayleigh statistics, namely the K-distribution. We show that the K-distribution can be used to describe the envelope of the echo, and its parameters may be used to distinguish between different regions in ultrasonic B-scan images. The validity of the model is tested using phantoms. Preliminary results indicate that the parameters of the K-distribution may be used to separate targets, in which the number of scatterers or the scattering cross-sections differ from that of the background. The method of employing the parameters of the K-distribution appears to be better than the methods based solely on the signal-to-noise ratio.

Advantages of subharmonic over second harmonic backscatter for contrast-to-tissue echo enhancement.

It is shown experimentally that backscatter from two ultrasonic contrast agents suspended in water or saline contains subharmonics of the incident frequency that are stronger than those backscattered at the same incident pressure from chicken breast. It is also shown that the ratio of subharmonic backscattered from contrast to that backscattered from tissue, is stronger than the ratio of backscattered second harmonic. In consequence, blood that contains contrast should be more easily detectable with respect to tissue if the subharmonic, rather than the second harmonic, is used for imaging.

Use of the K-distribution for classification of breast masses.

The K-distribution had been introduced as a valid model to represent the statistics of the envelope of the backscattered echo from phantom and tissue. This paper investigates the efficacy of the parameters of this statistical model; namely, the effective number and the effective cross-section, to characterize breast lesions as benign or malignant. Based on the normalized values of the effective number and the effective scattering cross-section, images containing benign and malignant masses were classified for a data set from 52 patients having breast masses/lesions. The receiver operating characteristic (ROC) curves were then obtained to test the classification based on these two parameters. The results indicate that the parameters of the K-distribution may be useful in classification of the breast lesions as benign and malignant.

Studies on the use of non-Rayleigh statistics for ultrasonic tissue characterization.

The research groups at Drexel University and Thomas Jefferson University had proposed the use of non-Rayleigh statistics for tissue characterization. Previous work based on the hypothesis that the envelope of the backscattered echosignal from abnormal regions of the tissue is more likely to be K-distributed than Rayleigh distributed, used the parameter of the K-distribution, M, to distinguish between regions containing benign or malignant masses and normal ones. In this work the B-scan breast images of 19 patients were studied using this approach. Previous studies have also been extended to exploit the existence of non-uniform phase characteristics of the echosignal from scatterers with some regular spacings, such as those in a periodic or quasi-periodic alignment. Computer simulations were carried out to show that the phase statistics deviate significantly from uniform in the range of (0, 2 pi) if the imaging region contained a number of periodically aligned (regular lattice) scatterers along with a collection of randomly distributed scatterers resulting in a quasi-periodic arrangement. This methodology was then applied to B-scan images of the breasts to distinguish between benign and malignant masses. If benign lesions show some sort of quasi-periodic or regular structures in the tissue, they will present non-uniform phase characteristics while more randomly structured malignant masses will have uniform phase characteristics. It is seen that the K-distribution may be used to identify the abnormal regions in the breast images and information on the phase may be used to further separate the abnormal regions into benign and malignant ones.

Using phase information in ultrasonic backscatter for in vivo liver analysis.

In recent studies, it has been shown that information about scatterer spacing can be obtained from analyzing the phase of the ultrasound echo from various media. Such information proves to be useful when examining the ultrasonic backscatter from well-organized tissue, such as the liver. By quantifying the deviations in scatterer spacing and/or varying degrees of regularity, conclusions may be drawn about the underlying pathology of the tissue. This paper examines the physical basis of how the scatterer locations affect the phase of the data. Computer simulations were performed that mimic various scattering conditions and that display the effects of differing degrees of regularity, as well as increases in a diffuse random background scattering component. Results of studies on a phantom are also included to investigate and display the phase response under well-controlled scattering conditions. Finally, in vivo data taken from liver scans were analyzed. In this work, it was shown that the phase of the backscattered signal holds valuable information regarding the pathological state of liver tissue. It is suggested that this simple examination of the phase can be refined into a technique to be used as a method to consistently detect the onset of pathological change.

Comparisons of the Rayleigh and K-distribution models using in vivo breast and liver tissue.

There is a strong interest in finding out which statistical model is the most appropriate for describing the envelope of the backscattered ultrasonic echoes from different types of tissues. The Rayleigh model is commonly employed, but this requires conditions, such as the presence of large number of randomly located scatterers with fairly uniform cross-sections, that are not always met. However, our research indicates that a model based on the K-distribution may provide a better fit to empirical data over a range of scattering conditions than the standard Rayleigh model. In this study, we looked at the K-distribution as a descriptor of the backscattered envelope of the breast and liver tissues (in vivo). By examining data from various tissue regions, a goodness-of-fit test (a least squares error method) was used to determine whether a Rayleigh or K-distribution model is more appropriate. From a large group of patients and volunteer scans (a total of 72 subjects), the fit between the K-distribution and the data is shown to have a much smaller error than the Rayleigh model.

Classification of breast masses in ultrasonic B-mode images using a compounding technique in the Nakagami distribution domain.

Classification of masses in ultrasonic B-mode images of the breast tissue using "normalized" parameters of the Nakagami distribution was recently investigated. The technique, however, did not yield performances that were comparable to those of an experienced radiologist, and utilized only a single image for tissue characterization. Because radiologists commonly use two to four images of a mass for characterization, a similar procedure is developed here. A simple summation of the normalized Nakagami parameters from two different images of a mass is utilized for classification as benign or malignant. The performance of the normalized Nakagami parameters before and after the summation has been carried out through a receiver operating characteristic (ROC) study. The bootstrap procedure has been utilized to compute the mean and SD of the ROC area, A(z), obtained for each parameter. It has been observed that combining normalized Nakagami parameters from two images of the mass may help to improve classification performance over that from utilizing the parameters of just a single image. The performance of this automated parameter-based approach appears to match that of a trained radiologist.