Classification of Cortical Bone Thicknesses Based on RF Signal Spectral Analysis
Sultan, H.H., Grisan, E., Peralta, L. and Harput, S. (2022). Classification of Cortical Bone Thicknesses Based on RF Signal Spectral Analysis. 2022 IEEE International Ultrasonics Symposium (IUS). Venice, Italy 10 - 13 Oct 2022 IEEE. https://doi.org/10.1109/ius54386.2022.9958573
|Authors||Sultan, H.H., Grisan, E., Peralta, L. and Harput, S.|
Cortical bone thickness is an important biomarker of bone fragility that reveals the risk of fractures. However, ultrasound bone assessment is challenging due to the complex nature of bone, such as varying porosity and microarchitecture, and the large difference between bone and soft tissue acoustic impedances. The research objective of this study is to develop a method to estimate cortical bone thickness by using spectral analysis, while avoiding traditional speed of sound measurements' figures due to the porous structure of bone tissue. In this study, multi-frequency ultrasound acquisitions have been used to cover a wide range of bone thickness and porosity values. Frequency modulated chirp waveforms are used as a transmit signal to increase the measurement SNR and the continuous wavelet transformation (CWT) is employed for the spectral analysis. The feasibility of the proposed methodology is demonstrated on simulated datasets and via experiments using ex vivo bone tissue. The preliminary experimental results showed a potential for cortical thickness classification using the received RF data.
|Journal||IEEE International Ultrasonics Symposium, IUS|
|Digital Object Identifier (DOI)||https://doi.org/10.1109/ius54386.2022.9958573|
|Accepted author manuscript|
Classification of Cortical Bone Thicknesses Based on RF Signal Spectral Analysis_v5_HHS_SH_letter.docx
File Access Level
|Online||10 Oct 2022|
|10 Oct 2022|
|Publication process dates|
|Deposited||17 Jan 2023|
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