Window-modulated compounding Nakagami imaging for ultrasound tissue characterization

Tsui, Po-Hsiang; Ma, Hsiang-Yang; Zhou, Zhuhuang; Ho, Ming-Chih; Lee, Yu-Hsin

doi:10.1016/j.ultras.2014.04.024

Cited by 45 publications

(63 citation statements)

References 44 publications

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“…Envelope detection of ultrasound backscattered signals is an essential step in many ultrasonic applications, such as envelope statistics based tissue characterization [4][5][6][7][8][9][10]. Real-time envelope detection is desired for fast analysis of ultrasound RF signals.…”

Section: Discussionmentioning

confidence: 99%

“…The expression ( ) ( ) r t jr t + is referred to as the analytic signal or complex RF echo. In previous studies, Hilbert transform has been frequently used for envelope detection of ultrasound RF signals [6][7][8][9][10]. Based on the property of Hilbert transform [17,18], the analytic signal ( ) ( ) r t jr t + has no spectrum components at negative frequencies and its spectrum components at positive frequencies are doubled [19].…”

Section: Envelope Detectionmentioning

confidence: 99%

“…Constructed from the amplitude of ultrasound echo signals, ultrasound B-mode images suffer from the drawbacks as being qualitative and operator-dependent [1]. To complement B-mode imaging, quantitative ultrasound (QUS) explores frequency, phase, or statistical information of backscattered ultrasound signals for tissue characterization [3][4][5][6][7][8][9][10]. In the context of QUS, parameters including backscatter coefficient, acoustic attenuation, speed of sound, envelope statistics, scatterer properties, and tissue elasticity can be quantified for tissue characterization [4,11,12].…”

Section: Introductionmentioning

confidence: 99%

“…Envelope statistics are directly related to tissue microstructures and are able to characterize structural alterations in tissues that are not apparent on ultrasound B-mode images [4][5][6][7][8][9][10]. Thus, they are useful for quantitative description of pathological state of tissues.…”

Section: Introductionmentioning

confidence: 99%

“…Thus, they are useful for quantitative description of pathological state of tissues. Envelope detection of ultrasound RF data is essential for envelope statistics analysis [4][5][6][7][8][9][10]. In order to ensure real-time backscattered envelope analysis, the time efficiency of the envelope detection algorithm is demanded.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Real-time envelope detection of ultrasound radiofrequency signals using OpenCV GPU framework

Zhou¹,

Wang²,

Shuicai³

et al. 2017

Med Devices Diagn Eng

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Section: Discussionmentioning

confidence: 99%

Section: Envelope Detectionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Real-time envelope detection of ultrasound radiofrequency signals using OpenCV GPU framework

Zhou¹,

Wang²,

Shuicai³

et al. 2017

Med Devices Diagn Eng

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Association Between Muscle Strength and Modeling Estimates of Muscle Tissue Heterogeneity in Young and Old Adults

Harris‐Love

Gonzales

Wei

et al. 2018

J of Ultrasound Medicine

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Objectives-Assessing aging muscle through estimates of muscle heterogeneity may overcome some of the limitations of grayscale analyses. The objectives of this study included determining statistical model parameters that characterize muscle echogenicity and are associated with strength in younger and older participants.Methods-Thirty-three community-dwelling participants were assigned to younger and older groups. Quantitative B-mode ultrasound scanning of the rectus femoris and isometric grip strength testing were completed. Shape or dispersion parameters from negative binomial distribution, Nakagami, gamma, and gamma mixture models were fitted to the grayscale histograms.Results-The mean ages ± SDs of the younger and older groups were 24.0 ± 2.3 and 65.1 ± 6.5 years, respectively. Statistical model shape and dispersion parameters for the grayscale histograms significantly differed between the younger and older participants (P = .002-.006). Among all of the statistical models considered, the gamma mixture model showed the best fit with the grayscale histograms (χ 2 goodness of fit = 62), whereas the Nakagami distribution displayed the poorest fit (χ 2 goodness of fit = 2595). Grayscale values were significantly associated with peak grip strength force in younger adult participants (R 2 = 0.36; P < .008). However, the negative binomial dispersion parameter k (adjusted R 2 = 0.70; P < .001) and gamma shape parameter α (adjusted R 2 = 0.68; P < .01) showed the highest associations with peak grip strength force in older adult participants.Conclusions-The negative binomial dispersion parameter k and the gamma shape parameter α have clinical relevance for the assessment of age-related muscle changes. Statistical models of muscle heterogeneity may characterize the association between muscle tissue composition estimates and strength better than grayscale measures in samples of community-dwelling older adults.

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Numerical and experimental investigation of impacts of nonlinear scattering encapsulated microbubbles on Nakagami distribution

et al. 2019

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Purpose The Nakagami statistical model and Nakagami shape parameter m have been widely used in linear tissue characterization and preliminarily characterized the envelope distributions of nonlinear encapsulated microbubbles (EMBs). However, the Nakagami distribution of nonlinear scattering EMBs lacked a systematical investigation. Thus, this study aimed to investigate the Nakagami distribution of EMBs and illustrate the impact of EMBs' nonlinearity on the Nakagami model. Method A group of simulated EMB phantoms and in vitro EMB dilutions with an increasing concentration distribution under various EMB nonlinearities, as regulated by acoustic parameters, were characterized by using the window‐modulated compounding Greenwood–Durand estimator. Results Raw envelope histograms of simulated and in vitro EMBs were well matched with the Nakagami distribution with a high correlation coefficient of 0.965 ± 0.021 (P < 0.005). The mean values and gradients of m parameters of simulated and in vitro EMBs were smaller than those of linear scatterers due to the stronger nonlinearity. These m values exhibited a quasi‐linear improvement with the increase in second harmonic nonlinear‐to‐linear component ratio regulated by pulse lengths and excitation frequencies at low‐ and high‐concentration conditions. Conclusions The Nakagami distribution was suitable for the EMBs characterization but the corresponding m parameter was affected by the EMBs' nonlinearity. These validations provided support and nonlinear impact assessment for the EMBs' characterization using the Nakagami statistical model in the future.

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Window-modulated compounding Nakagami imaging for ultrasound tissue characterization

Cited by 45 publications

References 44 publications

Real-time envelope detection of ultrasound radiofrequency signals using OpenCV GPU framework

Real-time envelope detection of ultrasound radiofrequency signals using OpenCV GPU framework

Association Between Muscle Strength and Modeling Estimates of Muscle Tissue Heterogeneity in Young and Old Adults

Numerical and experimental investigation of impacts of nonlinear scattering encapsulated microbubbles on Nakagami distribution

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