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Ultrasound Characterization of Cortical Bone Using Shannon Entropy.
- Source :
-
Ultrasound in Medicine & Biology . Aug2023, Vol. 49 Issue 8, p1824-1829. 6p. - Publication Year :
- 2023
-
Abstract
- Ultrasound backscattered signals encompass information on the microstructure of heterogeneous media such as cortical bone, in which pores act as scatterers and result in the scattering and multiple scattering of ultrasound waves. The objective of this study was to investigate whether Shannon entropy can be exploited to characterize cortical porosity. In the study described here, to demonstrate proof of concept, Shannon entropy was used as a quantitative ultrasound parameter to experimentally evaluate microstructural changes in samples with controlled scatterer concentrations made of a highly absorbing polydimethylsiloxane matrix (PDMS). Similar assessment was then performed using numerical simulations on cortical bone structures with varying average pore diameter (Ct.Po.Dm.), density (Ct.Po.Dn.) and porosity (Ct.Po.). The results suggest that an increase in pore diameter and porosity lead to an increase in entropy, indicating increased levels of randomness in the signals as a result of increased scattering. The entropy-versus-scatterer volume fraction in PDMS samples indicates an initial increasing trend that slows down as the scatterer concentration increases. High levels of attenuation cause the signal amplitudes and corresponding entropy values to decrease drastically. The same trend is observed when porosity of the bone samples is increased above 15%. Sensitivity of entropy to microstructural changes in highly scattering and absorbing media can potentially be exploited to diagnose and monitor osteoporosis. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 03015629
- Volume :
- 49
- Issue :
- 8
- Database :
- Academic Search Index
- Journal :
- Ultrasound in Medicine & Biology
- Publication Type :
- Academic Journal
- Accession number :
- 164416832
- Full Text :
- https://doi.org/10.1016/j.ultrasmedbio.2023.04.006