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Estimation of mean scatterer spacing based on autoregressive spectral analysis of pre-filtered echo data

Mean scatterer spacing (MSS) has been recognized as an effective tool for characterization and discrimination of tissues that present a semi-regular lattice of scatterers. The spectrum of the ultrasound echo of these tissues presents a number of harmonics due to the semi-regular scatterer distribution. A new algorithm for estimating the MSS by exploring the harmonic contents of the ultrasound echo is presented. This algorithm also provides a reliability indicator of the MSS estimate allowing for acceptance or rejection of the estimate. Simulations show that the acceptance criterion has been effective in reducing the standard deviation of the MSS estimates. In vitro experiments were conducted to illustrate the practical use of the proposed algorithm in the estimation of MSS.