Error analysis in acoustic elastography. II. Strain estimation and SNR analysis.

Accurate displacement estimates are required to obtain high-quality strain estimates in elastography. In this paper the strain variance is derived from the statistical properties of the displacement field to define a point signal-to-noise ratio for elastography (SNR0). Displacements caused by compressional forces applied along the axis of the transducer beam are modeled by scaling and shifting the axial reflectivity profile of the tissue. The strain variance is given as a function of essential experimental parameters, such as the amount of tissue compression, echo waveform window length, and the amount of window overlap. SNR0 is defined in terms of applied compression and strain variance and normalized by the input signal-to-noise ratio (SNRi) for echo signals, to formulate the performance metric SNR0/SNRi. This quantity characterizes the noise properties, dynamic range, and sensitivity of strain images based on the spatial resolution requirements. The results indicate that low noise, high sensitivity, and limited dynamic range strain images are obtained for high-frequency bandpass signals when the applied strain is small. For large strains, however, one strategy for low-noise strain imaging employs base-band signals to obtain images with large dynamic range but limited peak sensitivity and noise figure. A better strategy includes companding, which eliminates the average strain in the echo signal before cross-correlation to reduce the dynamic range requirement and increase peak sensitivity for strain estimates.

[1]  Correlation of Signals Having a Linear Delay , 1963 .

[2]  G. Clifford Carter,et al.  Estimation of time delay in the presence of source or receiver motion , 1977 .

[3]  W. Adams,et al.  Correlator compensation requirements for passive time-delay estimation with moving source or receivers , 1980 .

[4]  R. F. Wagner,et al.  Low Contrast Detectability and Contrast/Detail Analysis in Medical Ultrasound , 1983, IEEE Transactions on Sonics and Ultrasonics.

[5]  J. Betz,et al.  Comparison of the deskewed short-time correlator and the maximum likelihood correlator , 1984 .

[6]  John W. Betz Effects of uncompensated relative time companding on a broad-band cross correlator , 1985, IEEE Trans. Acoust. Speech Signal Process..

[7]  F. Kallel,et al.  Speckle motion artifact under tissue rotation , 1994, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[8]  A.R. Skovoroda,et al.  Tissue elasticity reconstruction based on ultrasonic displacement and strain images , 1995, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[9]  J. Ophir,et al.  Theoretical bounds on strain estimation in elastography , 1995, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[10]  C. Sumi,et al.  Estimation of shear modulus distribution in soft tissue from strain distribution , 1995, IEEE Transactions on Biomedical Engineering.

[11]  Faouzi Kallel,et al.  Tissue elasticity reconstruction using linear perturbation method , 1996, IEEE Trans. Medical Imaging.

[12]  M. Bilgen,et al.  Deformation models and correlation analysis in elastography. , 1996, The Journal of the Acoustical Society of America.

[13]  M. Bilgen,et al.  Error analysis in acoustic elastography. I. Displacement estimation. , 1997, The Journal of the Acoustical Society of America.