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Permanent link (DOI): https://doi.org/10.7939/R32P9S

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Ultrasonic imaging and cortical thickness determination of long bones Open Access

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Other title
Subject/Keyword
cortical thickness
inversion
Born appoximation
ultrasound velocity
osteoporosis
ultrasonic imaging
cortical bone
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Zheng, Rui
Supervisor and department
Sacchi, Mauricio D (Physics)
Wilman, Alan (Biomedical Engineering)
Le, Lawrence H (Radiology and Diagnostic Imaging)
Examining committee member and department
Lou, Edmond (Biomedical Engineering)
Lasaygues, Philippe (Laboratory of Mechanics and Acoustics, CNRS, Marseille, France)
Schmitt, Doug (Physics)
Chen, Jie (Electrical and Computer Engineering)
Department
Department of Physics & Department of Biomedical Engineering
Specialization

Date accepted
2011-09-29T03:32:35Z
Graduation date
2011-11
Degree
Doctor of Philosophy
Degree level
Doctoral
Abstract
Osteoporosis is a bone disease characterized by the degradation of mechanical competence and support of the skeleton, leading to fracture risk of the wrist, vertebrae, and hip. The disease is due to major decrease of mass and deterioration of micro-structure of bone tissues. In this study, bone imaging methodologies are developed to image the internal structure of long bones and to estimate particularly the top cortical thickness using zero-offset data acquired on the bone surface. The inversion algorithm, which requires a background velocity model, is based on Born scattering theory implemented with conjugate gradient iterative method to seek an optimal solution. In case the velocity model is multilayered, ray tracing through a smooth medium will be used to calculate the travelled distance and travelling time. Using the simulated data, the forward and adjoint operators of the inversion method are validated for its feasibility, accuracy, and quality of the reconstructed images. The values of some inversion variables, such as frequency range, frequency sampling rate, beam aperture, source wavelet, noise level, temporal sampling interval, pixel size, spacing interval of acquisition, and inversion regularization, are also investigated to optimize the quality of the reconstructed images. To image the top cortical layer, a good estimate of the background velocity can be obtained by linear regression method using the offset axial transmission data. The inversion algorithm is applied to image four real bone samples in vitro. The results demonstrate the top cortical interfaces can be reconstructed and correspond favorably to the CT image. The measurements show the sectional mean thickness (SMT) is a better and robust estimate for the average thickness of the cortex. The thicknesses of the bovine, cervine and ovine samples are 5, 4 and 3 mm, respectively, which correspond to absolute errors of 1.9%, 4.6% and 3.2% in comparison with the CT images. Due to the tissue absorption, interface curvature, and local heterogeneities, imaging the other interfaces was less successful. However, the current imaging method has successfully recovered the top cortical layer, offering a potential diagnostic tool to estimate cortical thinning for osteoporosis assessment.
Language
English
DOI
doi:10.7939/R32P9S
Rights
License granted by rui zheng (ruiz@ualberta.ca) on 2011-09-28T01:26:18Z (GMT): Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of the above terms. The author reserves all other publication and other rights in association with the copyright in the thesis, and except as herein provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
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