Biomedical Engineering and Bioengineering Commons^™

Diffuse Correlation Spectroscopy Measures Of Cerebral Blood Flow During Graded Hypoxia In Neonatal Piglets, Danielle Shoshany, Shadi Malaeb, Randolph Sinahon, Mert Deniz Polat, Meltem Izzetoglu, Patricia A. Shewokis, Kurtulus Izzetoglu

St. Chris Research Day

No abstract provided.

Evaluating Neuroimaging Modalities In The A/T/N Framework: Single And Combined Fdg-Pet And T1-Weighted Mri For Alzheimer’S Diagnosis, Peiwang Liu

McKelvey School of Engineering Theses & Dissertations

With the escalating prevalence of dementia, particularly Alzheimer's Disease (AD), the need for early and precise diagnostic techniques is rising. This study delves into the comparative efficacy of Fluorodeoxyglucose Positron Emission Tomography (FDG-PET) and T1-weighted Magnetic Resonance Imaging (MRI) in diagnosing AD, where the integration of multimodal models is becoming a trend. Leveraging data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), we employed linear Support Vector Machines (SVM) to assess the diagnostic potential of these modalities, both individually and in combination, within the AD continuum. Our analysis, under the A/T/N framework's 'N' category, reveals that FDG-PET consistently outperforms T1w-MRI across …

Microwave Imaging Technique For Breast Cancer Detection, Nure Alam Chowdhury

Theses and Dissertations

Breast cancer is a global problem, and it is inevitable to detect cancerous cells at early stages. In recent years, microwave imaging technology has been widely applied in biomedical applications for its non-ionizing radiation. In this study, we design a micro-strip patch antenna with an inverted T-type notch in the partial ground to detect tumor cells inside the human breast. The size of the current antenna is small enough (18 mm × 21 mm × 1.6 mm) to distribute around the breast phantom. The operating frequency has been observed from 6–14 GHz with a minimum return loss of −61.18 dB …

Advancements Of A Breast Tissue Marker And Localization System, Azrin Jamison

All Theses

Breast cancer has become the most prominent cancer worldwide in women. Annual mammograms are encouraged for women of high risk to increase early detection allowing for lumpectomies rather than mastectomies to occur. Prior to a lumpectomy, a biopsy must be taken to determine if the tissue is cancerous, and a breast cancer biopsy marker (BBM) is left in the region of possible cancerous tissue. Wire localization has been the gold standard for localizing these BBMs. However, due to the reported patient discomfort and logistical inefficiencies faced by healthcare providers (HCP), non-wire localization solutions have been recently developed. This study aims …

Secured Blockchain And Fractional Discrete Cosine Transform-Based Framework For Medical Images, Abhay Kumar Yadav, Virendra P. Vishwakarma

Makara Journal of Technology

Images can store large amounts of data and are useful for transmitting large amounts of information across different geographical locations using different cloud services. This data sharing increases the chances of cyber-attacks on digital images. Blockchain has properties that enable it to work as a solution to this problem, providing enhanced security and unchangeable storage. However, image size poses a challenge in image storage, as it increases the related storage cost. Compressing images using fractional discrete cosine transform (fctDCT) reduces the amount of data required to express an image securely. This paper presents a novel framework for securely storing and …

6d Single-Fluorogen Orientation-Localization Microscopy For Elucidating The Architecture Of Beta-Sheet Assemblies And Biomolecular Condensates, Tingting Wu, Weiyan Zhou, Jai S. Rudra, Rohit V. Pappu, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

We develop six-dimensional single-molecule orientation-localization microscopy (SMOLM) to measure the 3D positions and 3D orientations simultaneously of single fluorophores. We show how careful optimization of phase and polarization modulation components can encode phase, polarization, and angular spectrum information from each fluorescence photon into a microscope’s dipole-spread function. We used the transient binding and blinking of Nile red (NR) to characterize the helical structure of fibrils formed by designed amphipathic peptides, KFE8^L and KFE8^D, and the pathological amyloid-beta peptide Aβ42. We also deployed merocyanine 540 to uncover the interfacial architectures of biomolecular condensates.

Development Of An In Vitro 3-Dimensional Co-Culture Human Colorectal Cancer Model In Microfluidic Devices, Abby Jens

Master's Theses

Colorectal cancer is the second most common cause of cancer-related deaths in the United States, with the relative 5-year survival rate for distant stage cancer being only 14%. The most common treatment for colorectal cancer is with chemotherapeutic drugs; however, the discovery of these drugs is costly, time-consuming, and often requires the use of animal models that do not yield results that translate to clinical trials. Due to these shortcomings, researchers seek to develop physiologically relevant in vitro tumor models that more accurately mimic the tumor microenvironment for cheaper and faster high-throughput drug screening. The aim of this research was …

Comparison Of Scanning Electron Microscopy And Confocal Laser Microscopy For Tissue Surface Roughness Characterization, Tarnvir Dhaliwal

Master's Theses

It was found that the measurements captured by confocal microscopy and scanning electron microscopy had a statistically significant difference for bovine tissue. There was not a statistically significant for porcine and poultry tissue.

The intent of the study is to perform a comparative study to examine efficacy of two distinct technologies for a singular purpose: tissue surface roughness characterization. The two technologies compared are a confocal reflectance microscope and a scanning electron microscope. The comparison was made by comparing two surface roughness parameters [Ra and Rq] within ImageJ.

The study examined three different animal species [porcine, bovine, and poultry] to …

Implementing Unmanned Aerial Vehicles To Collect Human Gait Data At Distance And Altitude For Identification And Re-Identification, Donn E. Bartram

Graduate Theses, Dissertations, and Problem Reports

Gait patterns are a class of biometric information pertaining to the way a person moves and poses. Gait information is unique to each person and can be used to identify and reidentify people. Historically, this task has been achieved through the use of multiple ground-based imaging sensors. However, as Unmanned Aerial Vehicles (UAVs) advance, they present the opportunity to evolve the process of persons identification and re-identification. Collecting human gait data using UAVs at distances ranging from 20m to 500m and altitudes ranging from 0m to 120m is a challenging task. The current biometric data collection methods, primarily designed for …

Plasma Protein Signatures Of Adult Asthma, Gordon J. Smilnak, Yura Lee, Abhijnan Chattopadhyay, Annah B. Wyss, Julie D. White, Sinjini Sikdar, Jianping Jin, Andrew J. Grant, Alison A. Motsinger-Reif, Jian-Liang Li, Mikyeong Lee, Bing Yu, Stephanie J. London

Mathematics & Statistics Faculty Publications

Background: Adult asthma is complex and incompletely understood. Plasma proteomics is an evolving technique that can both generate biomarkers and provide insights into disease mechanisms. We aimed to identify plasma proteomic signatures of adult asthma.

Methods: Protein abundance in plasma was measured in individuals from the Agricultural Lung Health Study (ALHS) (761 asthma, 1095 non-case) and the Atherosclerosis Risk in Communities study (470 asthma, 10,669 non-case) using the SOMAScan 5K array. Associations with asthma were estimated using covariate adjusted logistic regression and meta-analyzed using inverse-variance weighting. Additionally, in ALHS, we examined phenotypes based on both asthma and seroatopy (asthma with …

Domain Adaptive Federated Learning For Multi-Institution Molecular Mutation Prediction And Bias Identification, W. Farzana, M. A. Witherow, I. Longoria, M. S. Sadique, A. Temtam, K. M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Deep learning models have shown potential in medical image analysis tasks. However, training a generalized deep learning model requires huge amounts of patient data that is usually gathered from multiple institutions which may raise privacy concerns. Federated learning (FL) provides an alternative to sharing data across institutions. Nonetheless, FL is susceptible to a few challenges including inversion attacks on model weights, heterogenous data distributions, and bias. This study addresses heterogeneity and bias issues for multi-institution patient data by proposing domain adaptive FL modeling using several radiomics (volume, fractal, texture) features for O6-methylguanine-DNA methyltransferase (MGMT) classification across multiple institutions. The proposed …