Cancellous bone supports the propagation of two compressional waves, commonly referred to as fast and slow waves, which can overlap in the acquired time-domain data. When such data are processed using conventional techniques, interference effects may cause artifacts to be present in the speed of sound and broadband ultrasound attenuation (BUA) measurements. Bayesian probability theory is a proposed method for extracting the ultrasonic properties of the individual fast and slow waves, even in the presence of substantial interference. In the current study, data were acquired in vitro at sites on a cancellous bone, and the acquired signals were used as input to a Bayesian probability approach for estimating parameters characterizing the fast and slow waves. For comparison, the signals were also processed using conventional methods. Although the conventionally obtained phase velocity and BUA frequently exhibited anomalous features, including negative dispersion, those estimated using probability theory exhibited no aberrant behavior. Hence, material properties obtained using Bayesian probability theory may provide more reliable estimates of bone quality and fracture risk than the apparent properties derived from the non-causal mixed mode signals. [Work supported by NIH R01HL40302 and R01AR057433, NSF CBET-0717830.]
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