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Attenuation is a key diagnostic parameter of tissue pathology change and thus may play a vital role in the quantitative discrimination of malignant and benign tumors in soft tissue. In this paper, two novel techniques are proposed for estimating the average ultrasonic attenuation in soft tissue using the spectral domain weighted nearest neighbor method. Because the attenuation coefficient of soft tissues can be considered to be a continuous function in a small neighborhood, we directly estimate an average value of it from the slope of the regression line fitted to the 1) modified average midband fit value and 2) the average center frequency shift along the depth. To calculate the average midband fit value, an average regression line computed from the exponentially weighted short-time Fourier transform (STFT) of the neighboring 1-D signal blocks, in the axial and lateral directions, is fitted over the usable bandwidth of the normalized power spectrum. The average center frequency downshift is computed from the maximization of a cost function defined from the normalized spectral cross-correlation (NSCC) of exponentially weighted nearest neighbors in both directions. Different from the large spatial signal-block-based spectral stability approach, a costfunction- based approach incorporating NSCC functions of neighboring 1-D signal blocks is introduced. This paves the way for using comparatively smaller spatial area along the lateral direction, a necessity for producing more realistic attenuation estimates for heterogeneous tissue. For accurate estimation of the attenuation coefficient, we also adopt a reference-phantombased diffraction-correction technique for both methods. The proposed attenuation estimation algorithm demonstrates better performance than other reported techniques in the tissue-mimicking phantom and the in vivo breast data analysis.

In this paper, a phase-based direct average strain estimation method is developed. A mathematical model is presented to calculate axial strain directly from the phase of the zero-lag cross-correlation function between the windowed precompression and stretched post-compression analytic signals. Unlike phase-based conventional strain estimators, for which strain is computed from the displacement field, strain in this paper is computed in one step using the secant algorithm by exploiting the direct phase-strain relationship. To maintain strain continuity, instead of using the instantaneous phase of the interrogative window alone, an average phase function is defined using the phases of the neighboring windows with the assumption that the strain is essentially similar in a close physical proximity to the interrogative window. This method accounts for the effect of lateral shift but without requiring a prior estimate of the applied strain. Moreover, the strain can be computed both in the compression and relaxation phases of the applied pressure. The performance of the proposed strain estimator is analyzed in terms of the quality metrics elastographic signal-to-noise ratio (SNRe), elastographic contrast-to-noise ratio (CNRe), and mean structural similarity (MSSIM), using a finite element modeling simulation phantom. The results reveal that the proposed method performs satisfactorily in terms of all the three indices for up to 2.5% applied strain. Comparative results using simulation and experimental phantom data, and in vivo breast data of benign and malignant masses also demonstrate that the strain image quality of our method is better than the other reported techniques.