Biomedical Commons^™

Wavelet-Based Harmonization Of Local And Global Model Shifts In Federated Learning For Histopathological Images, W. Farzana, A. Temtam, K. M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Federated Learning (FL) is a promising machine learning approach for development of data-driven global model using collaborative local models across multiple local institutions. However, the heterogeneity of medical imaging data is one of the challenges within FL. This heterogeneity is caused by the variation in imaging scanner protocols across institutions, which may result in weight shift among local models leading to deterioration in predictive accuracy of global model. The prevailing approaches involve applying different FL averaging techniques to enhance the performance of the global model, ignoring the distinct imaging features of the local domain. In this work, we address both …

Investigation Of Delta-Focused Ictal Electrical Source Imaging In Refractory Focal Epilepsy, Jared A. Rybarczyk

Theses and Dissertations--Electrical and Computer Engineering

Refractory focal epilepsy is characterized by the presence of seizures that cannot be controlled via anti-seizure medications. For patients suffering from this form of epilepsy, accurate identification of the seizure onset zone is a crucial step for many modalities of treatment. Electrical source imaging (ESI) allows for estimation of the seizure onset zone from electroencephalography. EEG feature extraction is an important step that can impact the final accuracy of source estimates. This work provides a review of 23 ictal ESI studies and proposes a delta-focused ictal ESI methodology. Our proposed delta-focused ictal ESI is implemented across 33 refractory focal epilepsy …

Nonuniform Sampling-Based Breast Cancer Classification, Santiago Posso

Theses and Dissertations--Electrical and Computer Engineering

The emergence of deep learning models and their success in visual object recognition have fueled the medical imaging community's interest in integrating these algorithms to improve medical diagnosis. However, natural images, which have been the main focus of deep learning models and mammograms, exhibit fundamental differences. First, breast tissue abnormalities are often smaller than salient objects in natural images. Second, breast images have significantly higher resolutions but are generally heavily downsampled to fit these images to deep learning models. Models that handle high-resolution mammograms require many exams and complex architectures. Additionally, spatially resizing mammograms leads to losing discriminative details essential …

Adversarial Training Based Domain Adaptation Of Skin Cancer Images, Syed Qasim Gilani, Muhammad Umair, Maryam Naqvi, Oge Marques, Hee-Cheol Kim

Electrical & Computer Engineering Faculty Publications

Skin lesion datasets used in the research are highly imbalanced; Generative Adversarial Networks can generate synthetic skin lesion images to solve the class imbalance problem, but it can result in bias and domain shift. Domain shifts in skin lesion datasets can also occur if different instruments or imaging resolutions are used to capture skin lesion images. The deep learning models may not perform well in the presence of bias and domain shift in skin lesion datasets. This work presents a domain adaptation algorithm-based methodology for mitigating the effects of domain shift and bias in skin lesion datasets. Six experiments were …

Multi-Magnetic Material Transcranial Magnetic Stimulation Coils Development And Electric Field Measurement & Modeling Using Machine Learning, Mohannad Tashli

Theses and Dissertations

Transcranial Magnetic Stimulation (TMS) is a safe, effective, and non-invasive therapy for treating several psychiatric and neurological disorders. TMS is Food and Drug Administration (FDA) approved treatment and is commonly applied to patients who do not respond to medications for the treatment of clinical depression, smoking cessation, obsessive-compulsive disorder and migraine. Recently, there has been an increase in the development of electromagnetic neuromodulation techniques targeted at enhancing the effectiveness of TMS devices for the treatment of mental diseases. In TMS stimulation, focality is an important factor which determines the specificity of the pulses induced in different brain tissues. The electromagnetic …

Recent Progress In Microrna Detection Using Integrated Electric Fields And Optical Detection Methods, Logeeshan Velmanickam, Dharmakeerthi Nawarathna

Electrical & Computer Engineering Faculty Publications

Low-cost, highly-sensitivity, and minimally invasive tests for the detection and monitoring of life-threatening diseases and disorders can reduce the worldwide disease burden. Despite a number of interdisciplinary research efforts, there are still challenges remaining to be addressed, so clinically significant amounts of relevant biomarkers in body fluids can be detected with low assay cost, high sensitivity, and speed at point-of-care settings. Although the conventional proteomic technologies have shown promise, their ability to detect all levels of disease progression from early to advanced stages is limited to a limited number of diseases. One potential avenue for early diagnosis is microRNA (miRNA). …

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 …

An Fpga-Based Eit System For Deep Space Medical Imaging, Kendall R. Farnham

Dartmouth College Ph.D Dissertations

Dangers associated with high radiation and microgravity exposure in space are critical challenges inhibiting us from exploring deep space and pursuing long-duration missions, as current medical systems are unable to monitor, diagnose, or treat tissue injury within physical spacecraft constraints and communication limits. Ultrasound (US) is the current imaging system used on the International Space Station, but this technology relies on telemedical support (or onboard artificial intelligence/autonomous capabilities) for both operation and diagnosis, posing challenges for crews isolated in deep space. Electrical impedance tomography (EIT) is a non-invasive, non-ionizing technology that produces images of the electrical properties of tissues and …

Integrating Therapy Into Play: Stand-On Ride-On For A Child With Cerebral Palsy, Kira Flanagan

UNF Graduate Theses and Dissertations

This study focuses on the development of an adaptive ride-on toy specifically designed for a 2.5-year-old child with spastic diplegic cerebral palsy. As a feasibility study, the primary objective of this innovative device is to enhance motor function, foster autonomy, and improve the overall quality of life for the child. The Power Mobility Device (PMD) integrates actuation and steering modifications, and a harness mechanism tailored to meet the child's unique needs. Comprehensive assessments of the child's spatiotemporal gait characteristics were conducted before and after a three-month usage period. The results reveal significant improvements in the child's ability to control dynamic …

Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia

Journal of Nonprofit Innovation

Urban farming can enhance the lives of communities and help reduce food scarcity. This paper presents a conceptual prototype of an efficient urban farming community that can be scaled for a single apartment building or an entire community across all global geoeconomics regions, including densely populated cities and rural, developing towns and communities. When deployed in coordination with smart crop choices, local farm support, and efficient transportation then the result isn’t just sustainability, but also increasing fresh produce accessibility, optimizing nutritional value, eliminating the use of ‘forever chemicals’, reducing transportation costs, and fostering global environmental benefits.

Imagine Doris, who is …

Design, Fabrication And Characterization Of Zero Power Sensor/Harvester For Smart Grid Applications, Zeynel Guler

Mechanical Engineering ETDs

This study presents a flexible sensor/harvester device to be used in both electromagnetic sensing and energy harvesting applications for smart grids. When a current passes through a wire, the sensor detects the magnetic field created by that current. The sensor magnet interacts with the wire magnetic field resulting in a transfer of energy through the piezoelectric cantilever. Piezoelectric, conductive, magnetic, and magnetostrictive composite thin films were prepared to fabricate this device.

Initially, the magnet of the cantilever was optimized considering its shape, thickness, length, taper angle etc. via both simulations and experiments. Peak to peak voltage versus cantilever position graph …

Adaptive Personalized Drug Delivery Method For Warfarin And Anemia Management: Modeling And Control., Affan Affan

Electronic Theses and Dissertations

Personalized precision medicine aims to develop the appropriate treatments for suitable patients at the right time to obtain optimal results. Personalized medicine is challenging due to inter- and intra-patient variability, narrow therapeutic window, the effect of other medications, comorbidity (more than one disease at a time), nonlinear patient dynamics, and time-varying patient dose response characteristics which include bleeding (internal and external). This research aims to develop a framework for an adaptive personalized modeling and control method with minimum clinical patient specific dose response data for optimal drug dosing. The proposed methodology is applied to anemia and warfarin management. It is …

Development Of A 3d Printed Conductive Biopolymer For Cardiac Tissue Engineering, Britanny Lizeth Stark

Open Access Theses & Dissertations

Cardiovascular disease (CVD) is the leading cause of death in the US, with approximately 859,000 deaths each year. The major contributor to CVD is Acute Myocardial Infarction (AMI), which causes the death of approximately 25% of the cardiomyocytes present in the left ventricle of the heart. After AMI, the adult human heart has a very limited regenerative capacity. Moreover, the electrical propagation of the myocardium is severely disrupted, making the heart more susceptible to failure and patient death. However, current pharmacological treatments do not address the loss of cardiomyocytes and the disruption of electrical propagation in the heart. Tissue engineering …

An Investigation Of Match For Lossless Video Compression, Brittany Sullivan-Reicks

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

A new lossless video compression technique, Match, is investigated. Match uses the similarity between the frames of a video or the slices of medical images to find a prediction for the current pixel. A portion of the previous frame is searched to find a matching context, which is the pixels surrounding the current pixel, within some distance centered on the current location. The best distance to use for each dataset is found experimentally. The matching context refers to the neighborhood of w, nw, n, and ne, where the pixel in the previous frame with the closest matching context becomes the …

Controlled Radiation Capsule For Precision And Rapid Cancer Treatment, Hoseon Lee, Zsolt Kollar, Bailey R. White, Junia Nguyen, David Roque, Sowjanya Palagani

Symposium of Student Scholars

This research aims to transform cancer treatment through the optimization of brachytherapy, with a focus on reducing treatment duration, setup complexities, and financial burdens, all while emphasizing patient safety. Patients living at a distance from radiation clinics, particularly those undergoing extended Low Dose Radiation brachytherapy, often struggle with the formidable financial challenges associated with securing nearby accommodations. In response to these issues, the research introduces a radiation capsule designed to condense the conventional six-month treatment period to approximately just one week, thereby significantly reducing the duration of required accommodations. This capsule is especially relevant considering the construction cost of $40 …

Improving Cellphone-Based Bio-Imaging Technique For Fluorescence Detection, Erteza T. Efaz

LSU Master's Theses

The research presented in this thesis focuses on the design, development, and evaluation of a fluorescence detection system. The system is implemented primarily as an Android application, Auto Camera, which leverages smartphone cameras to capture and analyze fluorescent images. The application provides a user-friendly interface with some configurable features like exposure time, ISO speed, and storage limit; as well as defining detection thresholds and setting acquisition intervals. This study begins with the architectural framework of the Android application, which is written in Java using Android Studio. The API compatibility is set to version 33, and users are prompted to grant …

Hierarchical Based Classifcation Method Based On Fusion Ofgaussian Map Descriptors Foralzheimer Diagnosis Using T1‑Weighted Magnetic Resonance Imaging, Nourhan Zayed, Shereen E. Morsy, Inas A. Yassine

Mechanical Engineering

Alzheimer’s disease (AD) is considered one of the most spouting elderly diseases. In 2015, AD is reported the US’s sixth cause of death. Substantially, non-invasive imaging is widely employed to provide biomarkers supporting AD screening, diagnosis, and progression. In this study, Gaussian descriptors-based features are proposed to be efcient new biomarkers using Magnetic Resonance Imaging (MRI) T1-weighted images to diferentiate between Alzheimer’s disease (AD), Mild Cognitive Impairment (MCI), and Normal controls (NC). Several Gaussian map-based features are extracted such as Gaussian shape operator, Gaussian curvature, and mean curvature. The aforementioned features are then introduced to the Support Vector Machine (SVM). …

Vertical Federated Learning Using Autoencoders With Applications In Electrocardiograms, Wesley William Chorney

Theses and Dissertations

Federated learning is a framework in machine learning that allows for training a model while maintaining data privacy. Moreover, it allows clients with their own data to collaborate in order to build a stronger, shared model. Federated learning is of particular interest to healthcare data, since it is of the utmost importance to respect patient privacy while still building useful diagnostic tools. However, healthcare data can be complicated — data format might differ across providers, leading to unexpected inputs and incompatibility between different providers. For example, electrocardiograms might differ in sampling rate or number of leads used, meaning that a …

Towards Reliable Hepatocytic Anatomy Segmentation In Laparoscopic Cholecystectomy Using U-Net With Auto-Encoder, Koloud Najem Alkhamaiseh

Dissertations

Despite the advantages of minimally invasive surgeries that depend heavily on vision, the indirect access and lack of the 3D field of view of the area of interest introduce some complications in the desired procedures. Fortunately, the recorded videos from these procedures offer the opportunity for intra-operative and post-operative analyses, to improve future performance and safety.

Deep learning models for surgical video analysis could therefore support visual tasks such as identifying the critical view of safety (CVS) in laparoscopic cholecystectomy (LC), potentially contributing to the reduction of the current rates of bile duct injuries in LC. Most bile duct injuries …

Auto-Segmentation In Pancreatic And Liver Radiation Therapy, Cenji Yu

Dissertations and Theses (Open Access)

Background

Gastrointestinal cancers exhibit a high mortality rate compared to other cancer types. Among these, pancreatic cancer ranks as the fourth leading cause of cancer-related deaths worldwide. The five-year survival rate remains alarmingly low at a mere 9%. Hepatocellular carcinoma (HCC), another aggressive form of cancer, is rapidly becoming the primary cause of cancer-related deaths in the United States. The treatment of both liver cancer and pancreatic cancer heavily relies on a multidisciplinary approach. Innovative treatment strategies involving dose-escalated regimens, such as stereotactic body radiation therapy (SBRT), are emerging as an important pillar of the management of liver and pancreatic …