Performance Evaluation of Ultrasonic Nakagami Image in Tissue Characterization

Conventional ultrasonic B-mode images qualitatively describe tissue structures but are unsuitable for quantitative analyses of scatterer properties. We have recently developed an ultrasonic parametric imaging technique based on the Nakagami statistical distribution that is able to quantify scatterer concentrations. The aim of the present study is to further explore both the behavior of a Nakagami image in characterizing different scatterer structures at different signal-to-noise ratios (SNRs) and the feasibility of Nakagami imaging using a general commercial ultrasound scanner for tissue examinations. Simulations, experiments on a tissue-mimicking phantom and in vitro measurements on a muscle tissue before and after microwave treatment were carried out. The SNR and contrast-to-noise ratio (CNR) were estimated to quantify image performance. The results demonstrate that a Nakagami image can differentiate different scatterer concentrations for single, hypoechoic and hyperechoic targets. Also, a Nakagami image, when combined with an ultrasound scanner, can complement the B-scan to characterize tissue and to identify the region of interest with a larger CNR. However, the noise effect can degrade the performance of a Nakagami image. When the signal SNR decreased to 15 dB in simulations and to 8 dB in experiments, the CNR of the hyperechoic Nakagami image decreased by 4% and 27%, respectively, and that of the hypoechoic one decreased by 42% and 80%, respectively. These results indicate that a Nakagami image behaves well in identifying regions with high scatterer concentrations but does not perform well when both the scatterer concentration and SNR are low.

[1]  C. Burckhardt Speckle in ultrasound B-mode scans , 1978, IEEE Transactions on Sonics and Ultrasonics.

[2]  B B Gosink,et al.  Accuracy of ultrasonography in diagnosis of hepatocellular disease. , 1979, AJR. American journal of roentgenology.

[3]  John W. Strohbehn,et al.  Probability density of myocardial ultrasonic backscatter , 1988, Proceedings of the 1988 Fourteenth Annual Northeast Bioengineering Conference.

[4]  E. Walach,et al.  Local tissue attenuation images based on pulsed-echo ultrasound scans , 1989, IEEE Transactions on Biomedical Engineering.

[5]  S Akselrod,et al.  The distribution of the local entropy in ultrasound images. , 1996, Ultrasound in medicine & biology.

[6]  P. Mohana Shankar,et al.  A general statistical model for ultrasonic backscattering from tissues , 2000, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[7]  P. Shankar A general statistical model for ultrasonic backscattering from tissues , 2000 .

[8]  B. Goldberg,et al.  Classification of ultrasonic B-mode images of breast masses using Nakagami distribution , 2001, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[9]  M. Srinivasan,et al.  Statistics of envelope of high-frequency ultrasonic backscatter from human skin in vivo , 2002, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[10]  Georgia D. Tourassi,et al.  General ultrasound speckle models in determining scatterer density , 2002, SPIE Medical Imaging.

[11]  Salvador Gonzalez,et al.  Quantitative ultrasonic methods for characterization of skin lesions in vivo. , 2003, Ultrasound in medicine & biology.

[12]  Shyh-Hau Wang,et al.  Quantitative analysis of noise influence on the detection of scatterer concentration by Nakagami parameter , 2005 .

[13]  Chien-Cheng Chang,et al.  Imaging local scatterer concentrations by the Nakagami statistical model. , 2007, Ultrasound in medicine & biology.

[14]  Chien-Cheng Chang,et al.  Feasibility study of using high-frequency ultrasonic Nakagami imaging for characterizing the cataract lens in vitro. , 2007, Physics in medicine and biology.