In vitro estimation of mean sound speed based on minimum average phase variance in medical ultrasound imaging

Yoon, Changhan; Lee, Yuhwa; Chang, Jin Ho; Song, Tai-Kyong; Yoo, Yangmo

doi:10.1016/j.ultras.2011.03.007

Cited by 54 publications

(31 citation statements)

References 19 publications

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“…The final form of the ultrasound echo signal is then determined by the characteristics of the scatters along the vertical scanning line. Considering a standard 10 MHz ultrasound scanner, the wavelength of ultrasound emitted from the scanner is around 26 μm as the average ultrasound velocity in human tissue is 1540 m/s1314151617181920. The human tissue on the scale of 26 μm are treated as continuous scattering media here.…”

Section: Resultsmentioning

confidence: 99%

Statistical Characterization of the Medical Ultrasound Echo Signals

Cai

2016

Sci Rep

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Medical ultrasound echo signals provide the basic information for obtaining the ultrasonic image in medical ultrasound technology. The statistics of the ultrasound echo signals reveals the systematic structure of the medical ultrasonic image via analyzing the corresponding statistical distributions. A novel statistical distribution, the ascending order K distribution, was proposed here to model the medical ultrasound echo signals. The ascending order K distribution was developed in light of the statistical analysis of the sequential waveforms in the echo signals. Comparison with the previous statistical distributions was made to verify the superiority of the ascending order K distribution. Further discussion showed the determination of the statistical principles for the ultrasound signals can enhance our understanding of the statistical principles of the ultrasound imaging, and thus, facilitate the optimization of the ultrasound image and the tissue identification in the ultrasound diagnosis.

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Section: Resultsmentioning

confidence: 99%

Statistical Characterization of the Medical Ultrasound Echo Signals

Cai

2016

Sci Rep

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“…Using the correct mean sound speed can be an alternative solution for minimizing the phase distortions and enhancing the image quality in medical ultrasound imaging. Various algorithms for estimating sound speed have been proposed [14][15][16][17][18][19][20], and beam-tracking-based sound speed estimation methods using two transducers has been proposed [15,16]. This method can provide accurate local sound speeds; however, its clinical application is limited since the method uses two transducers.…”

Section: Introductionmentioning

confidence: 99%

“…More recently, region-of-interest (ROI)-based optimal mean sound speed estimation methods have been proposed as a viable solution [14,19,20]. In these methods, the optimal mean sound speed that can produce the best focusing performance in the ROI is estimated rather than the actual sound speed in specific tissue type.…”

Section: Introductionmentioning

confidence: 99%

“…The optimal mean sound speed is estimated using a lateral spatial fast Fourier transform (FFT) magnitude of beamformed data as the focusing quality factor [19]. Phase variations at each pre-beamformed RF channel data and coherent factors have been proposed as focusing quality factors to estimate the mean sound speed [14,20]. These methods have shown that image quality in the ROI can be improved by using optimal the mean sound speed in beamforming.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Computationally Efficient Mean Sound Speed Estimation Method Based on an Evaluation of Focusing Quality for Medical Ultrasound Imaging

et al. 2019

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Generally, ultrasound receive beamformers calculate the focusing time delays of fixed sound speeds in human tissue (e.g., 1540 m/s). However, phase distortions occur due to variations of sound speeds in soft tissues, resulting in degradation of image quality. Thus, an optimal estimation of sound speed is required in order to improve image quality. Implementation of real-time sound speed estimation is challenging due to high computational and hardware complexities. In this paper, an optimal sound speed estimation method with a low-cost hardware resource is presented. In the proposed method, the optimal mean sound speed is determined by measuring the amplitude variance of pre-beamformed radio-frequency (RF) data. The proposed method was evaluated with phantom and in vivo experiments, and implemented on Virtex-4 with Xilinx ISE 12.4 using VHDL. Experiment results indicate that the proposed method could estimate the mean optimal sound speed and enhance spatial resolution with a negligible increase in the hardware resource usage.

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“…To improve B-mode image quality, a mean sound speed, that provides the optimum focusing based on minimizing the average phase variance or maximizing the mean spectral energy of the focused radio-frequency (RF) data with different sound speeds has been proposed [5][6]. This paper proposes an automatically selected mean sound speed when the PA signals are optimally focused.…”

Section: Introductionmentioning

confidence: 99%

Photoacoustic image reconstruction quality enhancement based on optimum focusing by calculating mean acoustic sound-speed

Cong

Kondo

Yamakawa

et al. 2014

2014 IEEE International Ultrasonics Symposium

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A constant sound speed of 1540 m/s is generally used in various photoacoustic image reconstruction algorithms, based on the assumption of homogeneous sound speed in human tissue. However, the variations of sound speeds in human tissue can be as great as 10%, which can lead to distortion and blurring in the reconstruction images. To enhance the reconstructed photoacoustic image quality, an automatically selected the mean sound speed based on optimum focusing of detected photoacoustic signals is proposed. The optimum focusing is quantified by calculating the minimum average sum of the deviation of focused photoacoustic signals from the mean with various sound speeds. The method is demonstrated using homogeneous and heterogeneous sound speed numerical simulation models. The central vertical and lateral profiles of reconstructed images verify the performance of the proposed method.

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In vitro estimation of mean sound speed based on minimum average phase variance in medical ultrasound imaging

Cited by 54 publications

References 19 publications

Statistical Characterization of the Medical Ultrasound Echo Signals

Statistical Characterization of the Medical Ultrasound Echo Signals

A Computationally Efficient Mean Sound Speed Estimation Method Based on an Evaluation of Focusing Quality for Medical Ultrasound Imaging

Photoacoustic image reconstruction quality enhancement based on optimum focusing by calculating mean acoustic sound-speed

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