Laksis Dans, Tatarinovs Aleksejs, Freivalds Kārlis. Wavelet transform based decomposition of ultrasound signals for cortical bone model evaluation. EUSIPCO 2024 32nd EUROPEAN SIGNAL PROCESSING CONFERENCE , 1496-1500 pp. 2024.
Bibtex citation:
Bibtex citation:
@inproceedings{16916_2024,
author = {Laksis Dans and Tatarinovs Aleksejs and Freivalds Kārlis},
title = {Wavelet transform based decomposition of ultrasound signals for cortical bone model evaluation},
journal = {EUSIPCO 2024 32nd EUROPEAN SIGNAL PROCESSING CONFERENCE },
pages = {1496-1500},
year = {2024}
}
author = {Laksis Dans and Tatarinovs Aleksejs and Freivalds Kārlis},
title = {Wavelet transform based decomposition of ultrasound signals for cortical bone model evaluation},
journal = {EUSIPCO 2024 32nd EUROPEAN SIGNAL PROCESSING CONFERENCE },
pages = {1496-1500},
year = {2024}
}
Abstract: With the global population aging, there is a growing demand for precise, cost-effective, and accessible methods to assess cortical bones for diagnosing degenerative bone conditions like osteoporosis. This article delves into innovative techniques for decomposing ultrasound signals to enhance current state-ofthe-art methodologies. Our approach focuses on deriving quantitative parameters for evaluating bone model characteristics.
Utilizing ultrasound scans of bone model surfaces, acquired signals undergo continuous wavelet transform. Subsequently, we extract two key parameters pertinent to bone models: cortical speed of sound and cumulative magnitude sum. Through this methodology, we aim to contribute to advancements in the assessment of cortical bone health.