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Objective: the purpose of this paper was to investigate the effect of spectral computation methods on the estimation of the four ultrasonic backscatter parameters, namely, the apparent integrated backscatter (AIB), the zero frequency intercept of apparent backscatter (FIAB), the frequency slope of apparent backscatter (FSAB), and the backscatter spectral centroid shift (SCS) from the backscattered signal of interest (SOI), and their subsequent correlations with cancellous bone parameter [bone volume/total volume (BV/TV)]. Methods: ultrasonic backscatter measurements were performed on 26 bovine cancellous bone specimens using a 1.0-MHz focused transducer. Four spectral estimation algorithms, including the classical periodogram, the autoregressive (AR) Burg algorithm, the AR covariance algorithm, and the AR modified covariance algorithm, were used to calculate the ultrasonic parameters. Influence of the signal’s delay time (T1) and its length (T2) on the strength of correlation between BV/TV and backscatter parameters was also studied. Results: the results have demonstrated that the AR-based estimators provide much more reliable and stronger correlations between the BV/TV and backscatter parameters than the classical periodogram. Recommendations for choosing SOI were also suggested. Conclusion: these results indicate that the AR-based method has a promising potential to enhance the performance of evaluation and diagnosis of the cancellous bone using the ultrasonic backscatter method. Significance: the enhancement of the correlation may provide a positive impact on the ultrasonic backscatter method to diagnose and monitor the bone quantity.

Effect of Spectral Estimation on Ultrasonic Backscatter Parameters in Measurements of Cancellous Bones