Wavelet transform-based strain estimator for elastography

A new signal processing algorithm based on a wavelet transform (WT) is prop osed for instantaneous strain estimation in acoustic elastography. The prop osed estimator locally weighs ultrasonic echo signals acquired before tissu e compression by a Gaussian window function and uses the resulting waveform as a mother wavelet to calculate the WT of the postcompression signal. Fro m the location of the WT peak, strain is estimated in the time-frequency do main. Because of the additive noise in signals and the discrete sampling, e rrors are commonly made in estimating the strain. Statistics of these error s are analyzed theoretically to evaluate the performance of the proposed es timator. The strain estimates are found to be unbiased, but error variances depend on the signal properties (echo signal-to-noise ratio and bandwidth) , signal processing parameter (time-bandwidth product), and the applied str ain. The results are compared with those obtained from the conventional str ain estimator based on time-delay estimates. The proposed estimator is show n to offer strain estimates with greater precision and potentially higher s patial resolution, dynamic range, and sensitivity at the expense of increas ed computation time.