Ultrasonic guided wave techniques have been researched and developed for characterization of cortical bone to evaluate bone health. Compared with the current “gold-standard” X-ray-based diagnostic modalities, ultrasound-based methods pose some advantages such as compactness, low cost, lack of ionizing radiation, and their ability to detect the mechanical properties of the cortex. Axial transmission technique with a source-receiver offset is employed to acquire the ultrasound data. The dispersion characteristics of the guided waves in bones are normally analyzed in the transformed domains using the dispersion curves. The transformed domain can be time-frequency representation using a single channel or wavenumber-frequency (or phase velocity-frequency) map with multi-channels. In terms of acquisition effort, the first method is more cost- and time-effective than the latter. However, it remains unclear whether single-channel dispersion analysis can provide as much quantitative guided-wave information as the multi-channel analysis.

The objective of this study is to compare the two dispersion analysis methods using numerically simulated and ex-vivo data of a simple bovine bone plate and explore their advantages and disadvantages. To facilitate a fair comparison, both single- and multi-channel signal processing approaches are implemented using sparsity-constrained optimization algorithms to reinforce the focusing power and thus the dispersion-curve imaging resolution. While the single-channel data acquisition and processing are much faster than those of the multi-channel, modal identification and analysis of the multi-channel data are straightforward and more convincing.

This research work was published by theUltrasonic Imagingjournal in April 2021 under the title “Single versus multi-channel dispersion analysis of ultrasonic guided waves propagating in long bones”. Postdoctoral Fellow Tho N.H.T. Tran shares the first authorship with the intern student Feng He. Professor Lawrence H. Le and Professor Dean Ta are the corresponding authors. This study was supported by the National Natural Science Foundation of China, the Program of Shanghai Academic Research Leader, and the Natural Sciences and Engineering Research Council of Canada.(Tho N.H.T. Tran, Feng He, Zhenggang Zhang, Mauricio D. Sacchi, Dean Ta*, and Lawrence H. Le*, Ultrasonic Imaging, 43, 157-163, 2021)