Master of Science, The Ohio State University, 2009, Chemical Engineering

Electrical Capacitance Volume tomography (ECVT) is gaining increased attention as a tool for imaging and understanding multi-phase flow systems. ECVT has the advantage of providing qualitative and quantitative information of the dynamic flow behavior of the process under investigation. ECVT non-invasive sensors are potentially a useful tool for researchers in various process industries. Validation of ECVT images using other established measurement technologies is vital to establish confidence in the reliability of ECVT technology for quantitative measurements of multi-phase flow systems. Work in this thesis is focused on using different measurement techniques to validate ECVT imaging of similar flow systems. Specifically, Magnetic Resonance Imaging (MRI) and fiber optics probes are used here. MRI is a well established imaging tool that has the reputation of providing precise high resolution cross-sectional images. On the other hand, fiber optics probes provide local density and velocity information of multi-phase flows. The combination of both techniques to validate ECVT measurements is expected to provide an acceptable estimate of the accuracy of ECVT imaging.

Committee: Jacques Zakin PhD (Advisor); Robert Brodkey PhD (Committee Member) Subjects: Chemical Engineering; Electrical Engineering; Energy; Engineering

Doctor of Philosophy, The Ohio State University, 2006, Electrical Engineering

Electrical tomography techniques for process imaging are very prominent for industrial applications due to their low cost, safety, high capture speed, and suitability for different vessel sizes. Among electrical tomography techniques, electrical capacitance tomography has been the subject of extensive recent research due to its noninvasive nature and capability of differentiating between different phases based on permittivity distribution. Research in electrical capacitance tomography is inherently interdisciplinary, and areas of research in it can be categorized as: (1) sensor design, (2) hardware electronics, (3) and image reconstruction. Work presented in this dissertation includes developments in image reconstruction and sensor design. Work on image reconstruction presented in this dissertation include developments of both forward and inverse solutions. A feed forward neural network based forward solver has been developed for fast and relatively accurate forward solutions. The forward solver has been integrated into a Hopfield optimization reconstruction technique to provide a fully non-linear image reconstruction process. In addition, a 3D volume image reconstruction has been developed by extending the 2D it neural network multi objective image reconstruction technique (NN-MOIRT) to 3D applications, and inclusion of new objective functions tailored for 3D imaging. Developments on sensor related topics provided in this dissertation are 3D capacitance sensor designs for 3D imaging and non-invasive capacitance sensors for simultaneous permittivity/conductivity imaging. In the former case, a 3D sensor with axial variation in field distribution has been used for volume imaging based on the developed Hopfield 3D optimization image reconstruction. In the latter case, an extension of the conventional capacitance sensor based on capacitance and power measurements has been provided for simultaneous imaging of permittivity and conductivity distributions.

Committee: Fernando Teixeira (Advisor) Subjects:

Doctor of Philosophy, The Ohio State University, 2024, Vision Science

Purpose: To characterize any differences in the vasculature, cone photoreceptor packing geometry (CPG), retinal ganglion cell (RGC) packing and inner plexiform layer (IPL) thickness measures between subjects with diabetes mellitus (DM) without/no diabetic retinopathy (NDR) and age-similar healthy control subjects. Methods: Both NDR and healthy cohorts were enrolled. Optical coherence tomography angiography (OCTA) was used to assess vasculature at the macula. The following parameters were quantified; vessel density, vessel length density, and vessel density index (VDI) in three vascular plexuses, namely, the superficial vascular plexus, intermediate capillary plexus, and deep capillary plexus (DCP). The choriocapillaris (CC) flow deficit (FD) was also measured. OCTA images were binarized and processed to extrapolate the parafovea and parafoveal quadrants and the OCTA indices mentioned above. The CC was processed with six different radii to quantify FD. Adaptive optics (AO) - scanning laser ophthalmoscopy images were used to characterize cones based on five CPG indices, namely, cone density (CD), cone-to-cone spacing (CS), linear dispersion index (LDi), heterogeneity packing index (HPi) and percent of cells with six neighbors (hexagonal) at 3.6⁰ in the temporal retina (TR). AO - optical coherence tomography images were used to quantify integrity of the inner retina based on five neural indices, namely, RGC density (RGCD), RGC spacing (RGCS), IPL full thickness (IPLFT), IPL sublamina A thickness (SAT) and IPL sublamina B thickness (SBT) at 5⁰ in the TR. Results: No significant differences were found between the cohorts in the parafovea or parafoveal quadrants for any of the OCTA indices, although generally the NDR had reduced vasculature. In all eyes, statistically significant differences were found in the parafoveal FD across the six radii (p < 0.001). There were no significant differences in any of the CPG indices or IPL thickness indices between the cohort (open full item for complete abstract)

Committee: Stacey Choi (Advisor); Nathan Doble (Advisor); Deyue Yu (Committee Member); Matthew Reilly (Committee Member); Thomas Raasch (Committee Member); Colleen Cebulla (Committee Member) Subjects: Ophthalmology; Optics

Master of Science, The Ohio State University, 2024, Electrical and Computer Engineering

Tomography is an imaging modality which takes a collection of one dimensional measurements and reconstructs them into a two dimensional cross sectional image. Perhaps the most well known example is X-Ray Computed Tomography (CT), which can be found in most hospitals as a means of performing medical imaging, particu- larly in the search for tumors and soft tissue injuries. This is a form of hard-field tomography, in which the value of each pixel in the reconstructed image is unaffected by those surrounding it, due to the non scattering nature of the applied signal. While useful for medical purposes due to its high resolution, X-ray CT requires bulky, ex- pensive equipment, which mitigates its usefulness in many industrial settings. This issue has been addressed with Electrical Capacitance Tomography (ECT), which uses much smaller and cheaper hardware. Unfortunately, ECT operates at a much lower frequency than X-ray CT, causing a soft-field effect where the measurement at any given point is affected by the other points near it. This thesis intends to describe the physics of X-ray CT and ECT, along with the various image reconstruction processes. Direct and iterative methods will be covered for both modalities, and the use of level set methods and statistical methods will be examined.

Committee: Fernando Teixeira (Advisor); Kubilay Sertel (Committee Member) Subjects: Electrical Engineering

Master of Science, Miami University, 2021, Chemical, Paper and Biomedical Engineering

Newts have exceptional capability of regenerating the lens throughout their lifetime. Since the 1890s, lens regeneration has been documented with ex vivo imaging techniques only. For the first time, we demonstrate that Optical Coherence Tomography (SD-OCT) can capture the in vivo essential morphological characteristics with abundant dynamic features. Monitoring lens regeneration using a single newt is now possible. The results show that the lens originates below the pupillary margin of the middle dorsal region and its early regenerating lens has an irregular elliptical shape. The lens volume expands quadratically, where its regenerating rate is linear from 14 to 60 days post-lentectomy. These findings warrant future research for tailoring OCT to study newt lens regeneration in vivo dynamically.

Committee: Hui Wang Dr (Advisor); Katia Del Rio-Tsonis Dr (Committee Member); Justin Saul Dr (Committee Member) Subjects: Biomedical Engineering

Doctor of Philosophy, The Ohio State University, 2019, Electrical and Computer Engineering

Electrical capacitance tomography (ECT) is a widely used tomographic modality to image multiphase flows in the chemical and oil industry. Due to some distinct advantages, NASA and Department of Energy (DoE) also have a particular interest in ECT-based imaging technology. The image reconstruction problem in ECT is inherently non-linear, and imaging of multiphase flows holding water as continuous phase (i.e., water-dominated flows) is especially challenging for conventional ECT due to the high permittivity of water. In this dissertation, we introduce a new approach based on the multi-frequency excitation of ECT sensors for real-time monitoring of multiphase flows holding water as either the continuous phase or the dispersed phase. The proposed approach exploits the dielectric dispersion due to interfacial polarization commonly known as the Maxwell-Wagner-Sillars (MWS) effect, which is present in multiphase flows with at least one conducting phase. For water continuous multiphase flows, MWS-ECT enables us to image and continuously monitor the flow in the region of interest. We then implement an MWS-ECT-based imaging technique to decompose and continuously monitor multiphase flow mixture components (fractional areas or volumes) in mixtures containing dispersed conducting phases. Besides MWS-ECT, Displacement-Current Phase Tomography (DCPT) is another imaging modality to image multiphase flows containing water. DCPT is a relatively new imaging technique that can provide superior imaging quality if water is present. DCPT uses the same hardware and reconstruction technique as ECT and inherits almost all of its hardware and software advantages. In this work, we introduce a novel technique based on the MWS effect to improve the performance of DCPT applied to two-phase flow imaging. Moreover, due to recent developments in electrical capacitance volume tomography (ECVT), direct extraction of the volumetric images from the measured data is now possible. Unlike conventiona (open full item for complete abstract)

Committee: Fernando Teixeira Prof. (Advisor); Robert Burkholder Prof. (Committee Member); Kubilay Sertel Prof. (Committee Member) Subjects: Electrical Engineering

Master of Science (M.S.), University of Dayton, 2017, Electrical and Computer Engineering

As radar technology development advances and more devices are employed in traditional frequency allocation bands, such as the microwave portion of the frequency spectrum, users are increasingly struggling to operate amidst this spectrum congestion. With spectrum congestion on the rise, application performance degradation is progressively being realized due to scarce available bandwidth. Therefore, users, such as the 5G wireless community and the automotive industry, are exploring applications at higher portions of the frequency spectrum with such efforts being focused in the millimeter wave (MMW) frequency bands. A number of novel applications, such as full-body imaging and automotive collision avoidance systems, have been improved on or realized with the aid of MMW frequencies and their associated phenomenology. However, this portion of the spectrum lags, in some cases by orders of magnitude, far behind in research and development in comparison to other bands such as those found in the microwave region. Therefore, a clear need to aid the knowledge base and investigate MMW radar phenomenology has been undertaken in this thesis. The research this thesis documents concerns designing, building and, fielding a distributed aperture array W-band (MMW) radar system. This thesis details incrementing the current fielded radar system capability from mono-static to bi-static imaging configurations. An improved method for calibrating the radar system resulting in higher quality imagery is also documented. The defined radar system was designed with the goal of performing multi-static Tomographic imaging. The research covered in this thesis is the first step toward incrementing the fielded system to full maturity.

Committee: Michael Wicks (Committee Chair); Lorenzo Lo Monte (Committee Member); Howard Evans (Committee Member); Robert Penno (Committee Member); Andrew Bogle (Committee Member) Subjects: Electrical Engineering; Engineering

Master of Science, The Ohio State University, 2012, Dentistry

Objective: The objective of this study was to examine computed tomography's ability to assess the regional variation of bone mineralization in a human mandible. Methods: Ten mandibular sections from cadavers (81.5 +/- 12.1 yrs) were scanned using micro-computed tomography (micro-CT) with 27.2 micron voxel size and cone beam CT (CBCT) with 200, 300, and 400 micron voxel sizes. In addition, fifteen clinical CBCT images from young patients (18.9 +/- 3.3 yrs) were identified. After segmentation of bone voxels, the 3D alveolar bone (AB) and the basal cortical bone (CB) regions were digitally isolated. A histogram of gray levels, which is equivalent to degree of bone mineralization, was obtained from each region of the CT images. Mean, standard deviation (SD), coefficient of variation (COV), fifth percentile low and high of AB and CB regions were obtained. Percentage differences of the gray level parameters between AB and CB were then computed. Results: The AB region had significantly lower Mean, Low5 and High5 but significantly higher SD and COV than the CB region for all CT images (p<0.016). The percentage difference of all gray level parameters was not significantly different between CBCT images with different voxel sizes (p>0.111). However, all parameters were significantly lower for the old cadaver group than for the young patient group (p<0.001). Conclusions: CBCT and micro-CT provide comparable results in the assessment of regional variation of bone mineralization in the human mandible. The percentage difference relative to an internal reference (CB) can be used to examine different CBCT images for both cross-sectional and longitudinal comparisons.

Committee: Do-Gyoon Kim Dr. (Advisor); Allen R. Firestone Dr. (Committee Member); William M. Johnston Dr. (Committee Member) Subjects: Dentistry; Radiology

Doctor of Philosophy, The Ohio State University, 2010, Chemical and Biomolecular Engineering

Fluidized beds provide good mass and heat transfer characteristics, temperature homogeneity and high flowability of particles. Gas-solid fluidized beds have been employed extensively in chemical, petrochemical, metallurgical, food, and pharmaceutical industries. A comprehensive understanding of the complex hydrodynamics and transport phenomena in gas-solid fluidized beds are required for successful application of these systems in industry. Moreover, much of the fundamental research reported in the literature on gas-solid fluidization properties have been performed with large gas-solid fluidized beds. Little is known about gas-solid fluidization in the mini- and micro-scale channel sizes ranging from 10-3 m to 10-2 m and 10-4 m to 10-5 m, respectively. A comprehensive study on the hydrodynamics of gas-solid fluidization and the significant wall effect in the mini- and micro-channels is needed for micro-scale reactor design. In this study, the dynamic flow behaviors in gas-solid fluidized beds are investigated by using Electrical Capacitance Volume Tomography (ECVT). Several advanced cylindrical and bend ECVT sensors are developed for the measurements. The instantaneous properties of the shape of the jets, and volumetric solids holdup of three-dimensional horizontal gas and gas/solid mixture jetting in a 0.3 m ID bubbling gas-solid fluidized bed are qualified and quantified using ECVT. The prediction from a mechanistic model established in this study and the ECVT experiments both show that the maximum penetration length and width of the horizontal gas jet increase with the superficial gas velocity in the bed. The average solids concentrations in a 0.1 m ID and 0.3 m ID beds are consistent with each other, but are higher than that in a 0.05 m ID bed at a given superficial gas velocity. The bubble size determined from ECVT with a threshold value of 0.3 for the solids concentration is consistent with those from the literature. In a 0.05 m ID gas-solid circulating fluidiz (open full item for complete abstract)

Committee: Liang-Shih Fan PhD (Advisor); L. James Lee PhD (Committee Member); Isamu Kusaka PhD (Committee Member) Subjects: Chemical Engineering

Master of Science in Biomedical Sciences (MSBS), University of Toledo, 2013, College of Medicine

The ability of an imaging system to accurately identify patient anatomy and provide reliable tumor information is critical in the radiation treatment planning process. As image guided radiation therapy and adaptive radiation therapy become more prevalent in treatment procedures, the image quality of these systems could perhaps be a limiting factor in their effectiveness. This research is intended to explore the differences in image quality between two separate imaging modalities commonly used in radiation therapy. A Philips Gemini TF Big Bore PET/CT and Varian True Beam On-Board kV cone beam CT imager were both assessed using the Catphan 504 image quality phantom. Ten different tests were evaluated with the phantom using several routine imaging protocols from both systems. Overall, the image quality between the cone beam and CT system was fairly consistent with one another with the exception of the low contrast detectability measurements. The effects of scatter radiation and image noise significantly reduced the cone beams ability to detect low contrast objects which ultimately degraded its image quality compared to CT.

Committee: Michael Dennis PhD (Committee Chair); Ishmael Parsai PhD (Committee Member); Dianna Shydka PhD (Committee Member) Subjects: Medical Imaging

Master of Science, The Ohio State University, 2013, Comparative and Veterinary Medicine

Introduction/Purpose: Osteosarcoma (OSA) is a common cancer of dogs comprising approximately 80 to 85% of all canine skeletal tumors (6% of all canine tumors), and is also the 8th most common childhood cancer. Detection of pulmonary metastasis as early as possible is vital, since the presence of and progression or regression of pulmonary metastasis critically impacts prognosis and treatment. Thus pulmonary metastatic load is a method of determining treatment response in patients with osteosarcoma. An objective in vivo method for measuring the efficacy of treatments in preclinical models of OSA is currently lacking, with most studies involving euthanasia of mice at different time points to track the effect of treatment via histopathology. This strategy requires large numbers of mice and precludes the assessment of individual treatment response. Our purpose was to determine whether micro-computed tomography in conjunction with micro-positron emission tomography (µCT/PET) is more sensitive for the detection of pulmonary metastasis than µCT alone and whether active pulmonary metastatic load could be quantified using µPET. Methods: Twelve mice had canine OSA cells injected into their right tibias. Mice were imaged at 3 and 5 weeks post- injection. The µCT and µCT/PET combined images were evaluated for pulmonary metastasis at each time point and the results compared. Regions of interest (ROI) were drawn around the lungs on each µCT slice to create a volume of interest (VOI) for measurement of 18F-fluorodeoxyglucose (18F-FDG) uptake. The VOIs were applied to the corresponding co-registered µPET images. The standard uptake value (SUV) for the lungs was divided by the corresponding liver SUV. The SUV ratios were compared between time points for each mouse, and between mice within a given time point. Mice were euthanized after imaging at 5 weeks and histopathology and stereologic analysis were performed on paraffin-embedded sections of the lungs. Results: µCT images (open full item for complete abstract)

Committee: Matthew Allen Vet MB, PhD (Advisor); Tod Drost DVM, DACVR (Committee Member); Krista La Perle DVM, PhD, DACVP (Committee Member) Subjects: Biology; Comparative; Health Sciences; Medical Imaging

Master of Science, The Ohio State University, 2005, Graduate School

Committee: Not Provided (Other) Subjects:

PhD, University of Cincinnati, 2024, Engineering and Applied Science: Mechanical Engineering

One of the largest sources of uncertainty in the calculation of stopping power ratios for use in proton radiotherapy is the measurement of Hounsfield Units (HU) for the determination of electron density. The primary source of this uncertainty is due to the relative difference in scatter between the patient and electron density calibration phantoms. In this dissertation, I will show how anatomy adaptive CT number to electron density calibration curves can improve the accuracy of stopping power ratio tabulations for proton radiation therapy dosimetry. We will generate new curves by measuring realistic (anthropomorphic) phantoms, fabricated using realistic tissue equivalent materials that accurately represent the internal structure and tissue types of the pelvis. The goal of this research is to use the new realistic anthropomorphic phantoms to evaluate how patient scatter affects measured electron density curves.

Committee: Henry Spitz Ph.D. (Committee Chair); Jay Kim Ph.D. (Committee Member); Michael Lamba Ph.D. (Committee Member); Bruce Mahoney (Committee Member); Peter Sandwall Ph.D M.A B.A. (Committee Member); Michael Alexander-Ramos Ph.D. (Committee Member); Sam Glover Ph.D. (Committee Member) Subjects: Nuclear Physics

Master of Science in Computer Engineering, University of Dayton, 2024, Electrical and Computer Engineering

This study aims to incorporate some advantages of computed tomographic data into the chest X-ray deep lung segmentation paradigm. We do this by training a deep convolutional neural network on chest radiographs (a.k.a. X-rays) with manually drawn ground truth and an identical network on radiographs digitally reconstructed from computed tomographic data with ground truth generated for the given computed tomographic image using an automated morphological 3D lung segmentation algorithm. The resulting twin-network ensemble generates pairs of lung image segmentation labels for chest X-rays: 1) a “traditional” segmentation of the lungs encompassing the apparently low-density tissue and 2) a novel, “full” lung segmentation encompassing an expanded view of the lungs' position in a chest X-ray including those regions obscured by the heart, ribs, and viscera, in essence, a 2D projection of any portion of the 3D lung. These networks perform consistently, with mean Intersection-Over-Union scores of > 90% and > 95%, respectively, across five trials. By subjective analysis, the proposed lung segmentation approach shows satisfactory ability to generalize onto genuine check X-ray images. The proposed technique's high performance and robustness establish a precedent for applying computed tomographic data to automatic chest X-ray segmentation and present an opportunity to further refine existing computer-aided detection and diagnostic tools by considering the full lung.

Committee: Russell Hardie Ph.D. (Advisor); Barath Narayanan Ph.D. (Committee Member); Vijayan Asari Ph.D. (Committee Member); Eric Lam (Committee Member) Subjects: Artificial Intelligence; Bioinformatics; Computer Engineering; Computer Science; Electrical Engineering; Radiology

Doctor of Philosophy, The Ohio State University, 2023, Nuclear Engineering

Neutron radiography and computed tomography (CT) offer unique opportunities in the field of non-destructive evaluation (NDE) for both reactor-based and accelerator-based neutron sources. The most widely implemented and advanced state-of-the-art techniques in radiography and CT use X-ray sources. However, in scenarios where X-ray penetration or contrast among materials are limited, advanced thermal and fast neutron methods can offer additional insights. X-ray attenuation is generally minimal for materials with a low atomic number (Z) and increases as the atomic number grows. This characteristic can sometimes result in inadequate contrast for low-Z materials or excessive attenuation for high-Z materials. Thermal neutron radiography – using neutrons near the thermal equivalent energy of 0.025 eV – takes advantage of the variable thermal neutron capture cross sections as a function of Z to provide high contrast, especially for certain elements such as Li and B. Attenuation values for thermal neutrons do not tend to follow a specific trend which enables contrast to be high for specific combinations of elements or isotopes. However, these lower energy neutrons have difficulty penetrating thicker objects, and certain elements can become activated due to nuclear transformations. Fast neutron radiography (using ~MeV neutrons) exhibits a more consistent attenuation across varying Z values, potentially benefiting both low-Z and high-Z materials. The primary advantage of fast neutron radiography and CT lies in the ability of MeV neutrons to penetrate high-Z materials like lead and tungsten better than MeV X-rays. The main challenge is ensuring adequate contrast between materials and achieving high detection efficiency, since these high energy neutrons are so penetrating. Generally, the most probable interactions of elements with fast neutrons are elastic scattering interactions which tends to reduce activation of target materials compared to thermal neutron techniques. This can (open full item for complete abstract)

Committee: Lei Cao (Advisor); Nerine Cherepy (Committee Member); Praneeth Kandlakunta (Committee Member); Richard Vasques (Committee Member) Subjects: Nuclear Engineering; Radiation

PhD, University of Cincinnati, 2023, Engineering and Applied Science: Materials Science

Thermal shape memory alloys are a special class of materials that possess the unique ability of returning to their original shape on application of heat after being deformed. One such thermal shape memory alloy is the equiatomic binary alloy of nickel and titanium commonly known as Nitinol. Discovered in 1959 at the U.S. Naval Ordinance Laboratory by William J. Buehler, NiTi performs shape recovery via phase transformation from martensite to austenite upon sufficient heating and reverting back to martensite upon cooling. This property of NiTi finds application in thermal actuators, orthodontic implants, and cardiovascular stents to name a few. Despite such advantages, widespread commercialization of NiTi has been hindered for decades by two major obstacles: (i) it is difficult to produce without oxidation related issues and (ii) once produced it is difficult to process into the desired shape and size for particular applications by conventional techniques due to the pseudoelasticity of its B2 austenitic phase. On the shape memory front, NiTi suffers from slow actuation which prevents its use as a thermo-mechanical actuator when actuation needs to be performed in a time interval smaller than the time required for shape recovery. To solve the problem of oxidation, vacuum arc melting (VAM) and vacuum induction melting (VIM) techniques are traditionally used and precipitation hardening significantly improves the strength of NiTi wires by forming Ni4Ti3 precipitates. The actuation frequency can be improved by creation of extra surfaces for enhanced heat transfer. This can be accomplished by the introduction of porosity via implementing metallic foams or 3D printing. However, most thermo-mechanical actuator designs tend to be smaller in size and, hence, require internal parts made of NiTi to be even smaller. Such requirements place a constraint on the application of Nitinol as thermal actuators as it is difficult (open full item for complete abstract)

Committee: Ashley Paz y Puente Ph.D. (Committee Chair); Matthew Steiner Ph.D. (Committee Member); Jing Shi Ph.D. (Committee Member); Dinc Erdeniz Ph.D. (Committee Member) Subjects: Materials Science

Master of Science, The Ohio State University, 2023, Earth Sciences

If the front page of Nature, which has featured Thwaites Glacier and other retreating glaciers throughout recent years, has taught us anything, it is that the snow—the snow that supports one sixth of the world's population—is melting. Never has it been more important to quantify snow globally and regionally, on the ground and from space, macroscopically and microscopically (Sturm et al. 2017). Snow specific surface area (SSA) plays an essential role in measuring all the aspects of snow, including the remote sensing of snow, the energy budget, and avalanche mechanics (Carlsen et al., 2017; Cohen and Rind, 1991; Lemmetyinen et al., 2018; Warren, 1982). Unfortunately, the best ways of measuring SSA accurately are laboratory methods, which are both expensive and time-consuming. The IceCube, an in-situ tool for measuring SSA quickly in the field, offers a promising alternative. However, its margins of error are uncertain. This study collected large samples of rounded grains, rounding facets, faceted crystals, and small samples of other grain morphologies in order to evaluate the errors associated with measuring SSA using the IceCube and micro-computed tomography (micro-CT) in the context of a large-scale campaign. Micro-CT measurements were used as validation data; however, snow samples were stored in a cold room at -26 °C for four to five months. The effects of the long storage time on the samples is largely unknown, and this is a limitation of the study. Given the assumption that the SSA of the samples, excluding fresh snow and other fragile grain morphologies, did not change significantly, the IceCube was found to have a positive bias of ~5% with a spread of ~15% for rounded grains, rounding facets, and faceted crystals. For all grain morphologies sampled, the IceCube was found to have a positive bias of ~5% with a spread of ~16%. Errors associated with using micro-CT as a validation method for snow microstructure measurements were also evaluated. This study revealed (open full item for complete abstract)

Committee: Michael Durand (Advisor); Ian Howat (Committee Member); Lonnie Thompson (Committee Member) Subjects: Earth; Environmental Science; Geophysics; Hydrology; Physics; Statistics

Master of Sciences (Engineering), Case Western Reserve University, 2023, Biomedical Engineering

Ultrasound tomography (UT), previously shown to have high sensitivity for the diagnosis of breast cancer, provides 360-degree submillimeter-resolution speed-of-sound imaging for tissue characterization. The purpose of this study was to validate UT for the detection of prostate cancer. Following prostate MRI and biopsy, patients with prostate cancer underwent robotic-assisted radical prostatectomy and had their prostates subsequently scanned ex vivo in the UT device. Correlations between pathology and imaging were done using an 18-sector approach comparing UT and MRI images against wholemount histopathology. Across 15 cases on blinded sector-based analysis, UT had a sensitivity of 74% and specificity of 95%, while MRI had a sensitivity of 67% and specificity of 98%. Thus, in this initial series of 15 patients, UT demonstrated equal or better sensitivity for detection of cancer compared with MRI. Future work will assess these findings in a larger cohort, followed by in vivo studies with limited angle UT.

Committee: Aaron Fleischman (Committee Chair); Dominique Durand (Committee Member); Shetal Shah (Committee Member) Subjects: Biomedical Engineering; Medicine

Master of Science in Mechanical Engineering (MSME), Wright State University, 2022, Mechanical Engineering

Repairing airfoil blades is necessary to extend the life of turbine engines. Directed energy deposition (DED) additive manufacturing (AM) provides the ability to add material at a specific location on an existing component. In this work, AM repairs on Ti-6Al-4V airfoil blades were analyzed to determine what effect the repair will have on the blade performance in high cycle vibration fatigue testing. Targeted sections were cut out of airfoil blades near high stress locations and repaired using DED. To understand the defects that arose with this type of repair, computed tomography imaging was used to quantify the defects from the AM process. The blades were then tested until failure using vibration bending fatigue to simulate turbine engine loading conditions. Results suggest that understanding the impact of internal and surface level defects arising from the AM process is critical towards the implementation of AM repair in aerospace components under fatigue loading.

Committee: Joy Gockel Ph.D. (Advisor); Nathan Klingbeil Ph.D. (Committee Member); Onome Scott-Emuakpor Ph.D. (Committee Member) Subjects: Mechanical Engineering

MS, University of Cincinnati, 2022, Education, Criminal Justice, and Human Services: Information Technology-Distance Learning

Among other cancers worldwide, lung cancer is the leading cause of death. The lives that we lose every year to lung cancer are more than combined of those lost to pancreatic, breast, and prostate cancer. However, lung cancer receives the least amount of research funds for each life lost to cancer each year. Lung cancer receives $3,580 per lost life, pancreatic cancer receives $4796 per lost life, prostate cancer receives $8116 per lost life, and breast cancer receives $19050 per lost life. The survival rate for lung cancer patients is very low compared to other cancer patients. If doctors diagnose a patient with stage I lung cancer, the survival rate will be 55%, which means that the patient will most likely survive cancer for five or more years. However, the survival rate will drop to 5% if the patient is diagnosed with stage IV lung cancer. Diagnosing cancer at an early stage gives doctors more time for their treatment plan, increasing the survival rate or even becoming cancer-free. In this thesis, we aim to develop a deep learning model that will help doctors predict and diagnose lung cancer early to save more lives. This thesis proposes a 2D CNN architecture, using IQ-OTH/NCCD - Lung Cancer Dataset in Kaggle. The dataset consists of 1097 CT scan images, which include three classes, normal cases, malignant cases, and benign cases. The experiment shows that the model has achieved high performance with 99.45% accuracy, and 1.75% loss. The weighted average is 99% and 99% for the macro average. The proposed model can be a particularly useful tool to support radiologists' decisions in predicting and classifying lung cancer.

Committee: Nelly Elsayed Ph.D. (Committee Member); M. Murat Ozer Ph.D. (Committee Member); Zaghloul Elsayed Ph.D. (Committee Member) Subjects: Information Technology