ArticleIEEE International Ultrasonics Symposium : [proceedings]. IEEE International Ultrasonics Symposium2018
Inferring porosity from frequency dependent attenuation in cortical bone mimicking porous media.
Article in IEEE International Ultrasonics Symposium : [proceedings]. IEEE International Ultrasonics Symposium, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Artificial neural network to estimate micro-architectural properties of cortical bone using ultrasonic attenuation: A 2-D numerical study.Computers in biology and medicine · 2019Article
- Modeling ultrasound attenuation in porous structures with mono-disperse random pore distributions using the independent scattering approximation: a 2D simulation study.Physics in medicine and biology · 2019Article
- Predicting Structural Properties of Cortical Bone by Combining Ultrasonic Attenuation and an Artificial Neural Network (ANN): 2-D FDTD Study.Image Analysis and Recognition: International Conference, ICIAR ... : proceedings. ICIAR · 2019Article
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4 authors.
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Abstract
Osteoporosis affects porosity in cortical bone. Quantifying levels of osteoporosis by inferring the micro-architectural properties from ultrasonic wave attenuation in cortical bone has yet to be done. In this work we use a phenomenological, power law model to describe the frequency dependent attenuation in non-absorbing porous media mimicking a simplified cortical bone structure. We optimize this model to fit data generated using a finite-difference, time domain (FDTD) numerical simulation. Model parameters are estimated using an ordinary least squares (OLS) formulation of the inverse problem. With these we determine linear, functional relationships between the model parameter estimates and the micro-architectural parameters, pore density and pore diameter. These relationships allow us to infer ranges of porosity from simulated attenuation data. Repeating this process for attenuation data collected from cortical bone samples could allow one to characterize the micro-architectural properties of bone.
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