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An adaptive harmonic separation (HS) technique is proposed to overcome the limitations in conventional filtering techniques for ultrasound (US) tissue harmonic imaging (THI). Based on expectation-maximization source separation, the proposed HS technique adaptively models the depth-varying fundamental and harmonic components in the frequency domain and separates the two by applying their calculated posterior probabilities. Phantom experiments with a Tx center frequency of 2 MHz are conducted to evaluate the proposed HS-based US THI schemes. The phantom images show that the proposed single-pulse THI scheme utilizing the HS technique provides not only an average improvement of 19.2% in axial resolution compared to the conventional bandpass filtering scheme but also similar image quality to that of the conventional pulse-inversion (PI) scheme which requires two Tx/Rx sequences for each scan line. Furthermore, when combined with the PI technique, the HS technique provides a uniform axial resolution over the entire 170 mm imaging depth with an average improvement of 17.1% compared to the conventional PI scheme. These results show that the proposed adaptive HS technique is capable of improving both the frame rate and the image quality of US THI. [ABSTRACT FROM AUTHOR]

Highlights: [•] A new frequency compounding is proposed to enhance ultrasound image quality. [•] Optimal weighting factors are estimated for the compounding along imaging depth. [•] The performances were verified through phantom and in vivo experiments. [•] SNR was improved by maximally 4.8dB compared to the conventional method. [ABSTRACT FROM AUTHOR]

Abstract: A new lossless compression method using context modeling for ultrasound radio-frequency (RF) data is presented. In the proposed compression method, the combination of context modeling and entropy coding is used for effectively lowering the data transfer rates for modern software-based medical ultrasound imaging systems. From the phantom and in vivo data experiments, the proposed lossless compression method provides the average compression ratio of 0.45 compared to the Burg and JPEG-LS methods (0.52 and 0.55, respectively). This result indicates that the proposed compression method is capable of transferring 64-channel 40-MHz ultrasound RF data with a 16-lane PCI-Express 2.0 bus for software beamforming in real time. [Copyright &y& Elsevier]

Abstract: In medical ultrasound imaging, the frequency-dependent attenuation causes a downshift of the center frequency of transmitted ultrasound as it propagates through the body. The downshifting results in a considerable loss of signal-to-noise ratio (SNR) after quadrature demodulation (QDM) in which down-mixing and low pass filtering are involved. To overcome the problem, dynamic QDMs have been proposed, in which the change in the center frequency along the axial direction is obtained using autocorrelation-based spectral estimation and compensated in the QDM block. As an alternative, this paper proposes an adaptive dynamic QDM using the 2nd-order autoregressive model. The main advantage over the conventional dynamic QDMs is to use real radio-frequency (RF) data in the spectral estimation, while its counterparts require additional steps to obtain either complex RF signals or complex baseband signals. This allows the proposed method to be used with a minimal modification of signal processing blocks. The performances of the proposed method were evaluated through in vitro and in vivo experiments. The performances were also compared with those of the conventional dynamic QDM. From the experiments, it was learned that the proposed method improved SNR by maximally 7.8dB in the near field compared with the conventional dynamic QDM. In the far field, however, its SNR improvement is similar to its counterpart. This may be explained by the fact that the signal loss mainly results from the amplitude attenuation and the diffraction rather than the frequency downshift in the far field. In addition, the proposed method improved contrast resolution (CR) by at least 6.8%, compared with that of the conventional dynamic QDM. The experimental results demonstrated that the proposed method can be used to improve SNR and CR of ultrasound images in an effective manner. [Copyright &y& Elsevier]