Osteoporosis is a common bone disease that increases risk of low-trauma fractures associated with substantial morbidity, mortality, and financial costs. Clinically, osteoporosis is defined by low bone mineral density (BMD). BMD explains approximately 60-70% of the variance in bone strength. The remainder is due to the cumulative and synergistic effects of other factors, including trabecular and cortical bone micro-architecture. In vivo quantitative characterization of trabecular bone (TB) micro-architecture with high accuracy, reproducibility, and sensitivity to bone strength will improve our understanding of bone loss mechanisms and etiologies benefitting osteoporotic diagnostics and treatment monitoring processes. The overall aim of the Ph.D. research is to design, develop and evaluate new 3-D imaging processing algorithms to characterize the quality of TB micro-architectural in terms of topology, orientation, thickness and spacing, and to move the new technology from investigational research into the clinical arena. Two algorithms regarding to this purpose were developed and validated in detail - (1) star-line-based TB thickness and marrow spacing computation algorithm, and (2) tensor scale (t-scale) based TB topology and orientation computation algorithm. The TB thickness and marrow spacing algorithm utilizes a star-line tracing technique that effectively accounts for partial voluming effects of in vivo imaging with voxel size comparable to TB thickness and also avoids the problem of digitization associated with conventional algorithms. Accuracy of the method was examined on computer-generated phantom images while the robustness of the method was evaluated on human ankle specimens in terms of stability across a wide range of resolutions, repeat scan reproducibility under in vivo condition, and correlation between thickness values computed at ex vivo and in vivo resolutions. Also, the sensitivity of the method was examined by its ability to predict bone strength of cadaveric specimens. Finally, the method was evaluated in an in vivo human study involving forty healthy young-adult volunteers and ten athletes. The t-scale based TB topology and orientation computation algorithm provides measures characterizing individual trabeculae on the continuum between perfect plate and perfect rod as well as individual trabecular orientation. Similar to the TB thickness and marrow spacing computation algorithm, accuracy was examined on computer-generated phantoms while robustness of the algorithm across ex vivo and in vivo resolution, repeat scan reproducibility, and the sensitivity to experimental mechanical bone strength were evaluated in a cadaveric ankle study. And the application of the algorithm was evaluated in a human study involving forty healthy young-adult volunteers and ten patients with SSRI treatment. Beside these two algorithms, an image thresholding algorithm based on the class uncertainty theory is developed to segment TB structure in CT images. Although the algorithm was developed for this specific application, it also works effectively for general 2-D and 3-D images. Moreover, the class uncertainty theory can be utilized as adaptive information in more sophisticated image processing algorithms such as Snakes, ASMs and graph search.

The finite element method (FEM) has been widely applied to various medical imaging applications over the past two decades. The remarkable progress in high-resolution imaging techniques has allowed FEM to draw great research interests in computing trabecular bone (TB) stiffness from three-dimensional volumetric imaging. However, only a few results are available in literature on applying FEM to multi-row detector CT (MDCT) imaging due to the challenges posed by limited spatial resolution. The research presented here develops new methods to preserve TB structure connectivity and to generate high-quality mesh representation for FEM from relatively low resolution images available at MDCT imaging. Specifically, it introduced a space-variant hysteresis algorithm to threshold local trabecular structure that preserves structure connectivity. Also, mesh generation algorithms was applied to represent TB micro-architecture and mesh quality was compared with that generated by traditional methods. TB stiffness was computed using FEM simulation on micro-CT (µ-CT) and MDCT images of twenty two cadaveric specimens of distal tibia. Actual stiffness of those specimens were experimentally determined by mechanical testing and its correlation with computed stiffness was analyzed. The observed values of linear correlation (r2) between actual bone stiffness and computed stiffness from µ-CT and MDCT imaging were 0.95 and 0.88, respectively. Also, reproducibility of the FEM-based computed bone stiffness was determined from repeat MDCT scans of cadaveric specimens and the observed intra-class correlation coefficient was a high value of 0.98. Experimental results demonstrate the feasibility of application of FEM with high sensitivity and reproducibility on MDCT imaging of TB at distal tibia under in vivo condition.

High fidelity measurements are necessary to validate existing and future turbulence models for the purpose of producing the next generation of more efficient gas turbines. The objective of the present study is to conduct several different measurements of multi-row film cooling arrays in order to better understand the physics involved with injection of coolant through multiple rows of discrete holes into a flat plate turbulent boundary layer. Adiabatic effectiveness distributions are measured for several multi-row film cooling geometries. The geometries are designed with two different hole spacings and two different hole types to yield four total geometries. One of the four geometries tested for adiabatic effectiveness was selected for flowfield measurements. The wall and flowfield are studied with several testing techniques, including: particle image velocimetry, hot wire anemometry, pressure sensitive paint and discrete gas sampling.

Full-coverage film cooling is investigated both experimentally and numerically. First, surface measurements local of adiabatic film cooling effectiveness and heat transfer augmentation for four different arrays are described. Reported next is a comparison between two very common turbulence models, Realizable k-ε and SST k-ω, and their ability to predict local film cooling effectiveness throughout a full-coverage array. The objective of the experimental study is the quantification of local heat transfer augmentation and adiabatic film cooling effectiveness for four surfaces cooled by large, both in hole count and in non-dimensional spacing, arrays of film cooling holes. The four arrays are of two different hole-to-hole spacings (P/D = X/D = 14.5, 19.8) and two different hole inclination angles (α = 30◦ , 45◦ ), with cylindrical holes compounded relative to the flow (β = 45◦ ) and arranged in a staggered configuration. Arrays of up to 30 rows are tested so that the superposition effect of the coolant film can be studied. In addition, shortened arrays of up to 20 rows of coolant holes are also tested so that the decay of the coolant film following injection can be studied. Levels of laterally averaged effectiveness reach values as high as ¯η = 0.5, and are not yet at the asymptotic limit even after 20 − 30 rows of injection for all cases studied. Levels of heat transfer augmentation asymptotically approach values of h/h0 ≈ 1.35 rather quickly, iii only after 10 rows. It is conjectured that the heat transfer augmentation levels off very quickly due to the boundary layer reaching an equilibrium in which the perturbation from additional film rows has reached a balance with the damping effect resulting from viscosity. The levels of laterally averaged adiabatic film cooling effectiveness far exceeding ¯η = 0.5 are much higher than expected. The heat transfer augmentation levels off quickly as opposed to the film effectiveness which continues to rise (although asymptotically) at large row numbers. This ensures that an increased row count represents coolant well spent. The numerical predictions are carried out in order to test the ability of the two most common turbulence models to properly predict full coverage film cooling. The two models chosen, Realizable k − ε (RKE) and Shear Stress T ransport k − ω (SSTKW), are both two-equation models coupled with Reynolds Averaged governing equations which make several gross physical assumptions and require several empirical values. Hence, the models are not expected to provide perfect results. However, very good average values are seen to be obtained through these simple models. Using RKE in order to model full-coverage film cooling will yield results with 30% less error than selecting SSTKW.