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P M Shankar

Publications and source records attributed to P M Shankar.

At least 19 recordsLinked to original sources
PubMed2006

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.

Algorithms↗
PubMed2006

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.

Algorithms↗
PubMed2005

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.

Algorithms↗
PubMed2004

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.

Algorithms↗
PubMed2004

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.

Albumins↗
PubMed2003

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.

Adult↗
PubMed2003

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.

Algorithms↗
PubMed2002

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.

Algorithms↗
PubMed2002

Classification of ultrasonic B mode images of the breast using frequency diversity and Nakagami statistics.

The parameters of the Nakagami distribution have been utilized in the past to classify lesions in breast tissue as benign or malignant. To avoid the effect of operatorgain settings on the parameters of the Nakagami distribution, normalized parameters were utilized for the classification. The normalized parameter was defined as the ratio of the parameter at the site of the lesion to its average value over several regions away from the site. This technique, however, was very time consuming. In this paper, the application of frequency diversity and compounding is explored to achieve this normalization. Lesions are classified using these normalized parameters at the site. A receiver operating characteristic (ROC) analysis of the parameters of the Nakagami distribution has been conducted before and after compounding on a data set of 60 benign and 65 malignant lesions. The ROC results indicate that this technique can reasonably classify lesions in breast tissue as benign or malignant.

Biopsy↗
PubMed2002

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.

Breast Neoplasms↗
PubMed2001

Classification of ultrasonic B-mode images of breast masses using Nakagami distribution.

The Nakagami distribution was proposed recently for modeling the echo from tissue. In vivo breast data collected from patients with lesions were studied using this Nakagami model. Chi-square tests showed that the Nakagami distribution is a better fit to the envelope than the Rayleigh distribution. Two parameters, m (effective number) and alpha (effective cross section), associated with the Nakagami distribution were used for the classification of breast masses. Data from 52 patients with breast masses/lesions were used in the studies. Receiver operating characteristics (ROC) were calculated for the classification methods based on these two parameters. The results indicate that these parameters of the Nakagami distribution may be useful in classification of the breast abnormalities. The Nakagami distribution may be a reasonable means to characterize the backscattered echo from breast tissues toward a goal of an automated scheme for separating benign and malignant breast masses.

Acoustics↗
PubMed2001

Use of frequency diversity and Nakagami statistics in ultrasonic tissue characterization.

The Nakagami distribution was recently proposed as a generalized model for the envelope of the backscattered ultrasonic echo from tissue. The parameters of the Nakagami model were also shown to be useful in tissue characterization. This paper explores the possibility of enhancing the ability of these parameters for tissue characterization through the techniques of diversity and compounding. Frequency diversity has been used to create multiple versions of the envelope, which are then combined. This compounded envelope has been modeled, and its parameters have been analyzed. The ability of these new parameters to enhance tissue characterization is studied using computer simulation and experiments on tissue-mimicking phantoms. Results indicate that the use of frequency diversity and compounding may indeed improve the ability of the parameters of the Nakagami model to separate different number densities of scatterers. Therefore, it is suggested that such an approach may lead to better techniques in ultrasonic tissue characterization.

Biomedical Engineering↗
PubMed2001

Ultrasonic tissue characterization using a generalized Nakagami model.

The statistics of the backscattered ultrasonic echo from tissue have been described using Rayleigh, K, and Nakagami distributions. The Nakagami and K distributions, each with two parameters, can model the envelope reasonably well. However, a three-parameter distribution is likely to match the envelope of the backscattered echo much better than these two-parameter distributions. Starting with the Nakagami distribution and including an additional parameter to account for the tails of the density function, a generalized Nakagami distribution has been derived. Computer simulation of A-scans and analysis of data collected from tissue-mimicking phantoms show that the generalized Nakagami distribution fits the statistics of the echo of the envelope better than the Nakagami distribution. The parameters of the generalized Nakagami distribution appear to be far more sensitive to the scattering conditions than the parameters of the Nakagami distribution.

Models, Theoretical↗
PubMed2000

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.

Breast Neoplasms↗
PubMed1999

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.

Albumins↗
PubMed1999

Subharmonic backscattering from ultrasound contrast agents.

The ultrasonic contrast of blood in tissue, which is needed for ultrasonic estimation of tissue perfusion, can be increased by injecting the blood with bubbles or hollow microspheres. It has been shown that an even greater improvement in contrast can be obtained by using the subharmonic generated by irradiated microspheres. By obtaining analytical solutions to the modified RPNNP equation for a coated microbubble, the relationship between the physical parameters of the encapsulated bubble and the threshold pressure is established. The observed increase in the resonance frequency of a coated microsphere is explained by introducing the concept of "acoustic radius" of the encapsulated bubble. It is predicted that subharmonic generation in contrast agents requires a threshold insonifying pressure, and should be a minimum when microspheres are insonated at twice their resonance frequency. Experiments confirm the existence of this optimum incident frequency and of a reasonably low threshold pressure for the generation of the subharmonic. The existence of the low threshold pressures for subharmonic generation in contrast agents may prove to be very valuable in ultrasonic contrast imaging.

Contrast Media↗
PubMed1998

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.

Adult↗