Biomedical Commons^™

Evaluation Of The Alveolar Crest And Cemento-Enamel Junction In Periodontitis Using Object Detection On Periapical Radiographs, Tai Jung Lin, Yi Cheng Mao, Yuan Jin Lin, Chin Hao Liang, Yi Qing He, Yun Chen Hsu, Shih Lun Chen, Tsung Yi Chen, Chiung An Chen, Kuo Chen Li, Patricia Angela R. Abu

Ateneo Laboratory for Intelligent Visual Environments

The severity of periodontitis can be analyzed by calculating the loss of alveolar crest (ALC) level and the level of bone loss between the tooth’s bone and the cemento-enamel junction (CEJ). However, dentists need to manually mark symptoms on periapical radiographs (PAs) to assess bone loss, a process that is both time-consuming and prone to errors. This study proposes the following new method that contributes to the evaluation of disease and reduces errors. Firstly, innovative periodontitis image enhancement methods are employed to improve PA image quality. Subsequently, single teeth can be accurately extracted from PA images by object detection with …

Denoising And Super-Resolution Of In-Vitro 4e Flow Mri In A Stenotic Phantom Model Using Physics-Informed Neural Networks., Shrouk M. Wally

Electronic Theses and Dissertations

In recent years, the use of 4D flow MRI has revolutionized cardiovascular imag- ing by providing comprehensive data on blood flow dynamics over time. However, the limited spatial and temporal resolution of this imaging modality can hinder the accurate assessment of complex hemodynamic phenomena. This thesis explores the application of Physics-Informed Neural Networks (PINNs) to enhance the resolution of 4D flow MRI data, thereby improving its clinical utility. PINNs are a class of neural networks that integrate physical laws into their training process. By embedding these physics equations, PINNs can discover the underlying physics of fluid dynamics to produce more …

Novel Sensors, Algorithms And Metrics For Human-Robot Interaction., Henry Lee Reynolds

Electronic Theses and Dissertations

The increased presence and deployment of robotics in sectors such as the medical field results in the demand for robots to, directly and indirectly, interface with people and their environment, making human-robot interaction (HRI) a vital thrust of robotics research. Assistive robots, for example, aid humans in accomplishing tasks or by providing support in the workforce. As the demand for nurses and the aging population increases, the assistive robots deployed will be deeply rooted in environments that require constant interaction with humans. This work contributed to improving aspects of HRI through 1) Expanding accessibility of the methods used for interfacing …

Development Of 3d Human Cardiovascular And Cancer Tissue Model Within A Self-Driven Microfluidic Platform For Preclinical Drug Screening, Aibhlin Alexis Esparza

Open Access Theses & Dissertations

According to the American Heart Association and World Health Organization, cardiovascular diseases (CVDs) are the leading cause of death worldwide. Monolayer cell culture (2D) and animal models are conventional methods to study CVDs, however, they limit researcherâ??s ability to simulate the human cardiovascular cellular microenvironments and accurate predication of pharmaceutical drug responses. Human induced pluripotent stem cell derived cardiomyocytes (hiPSC-CMs), biomaterials, and microfluidic technologies can be combined to create a controlled, reproducible 3D platform to study physiologically-relevant cellular responses to biochemical and physical changes in the microenvironment. My dissertation work demonstrates the development of novel self-driven microfluidic devices designed with …

Modification Of Time-Domain Terahertz Spectroscopy System To Polarimetry Imaging System With Application To Human Breast Cancer Surgical Specimen, Nikita Gurjar

Graduate Theses and Dissertations

Breast-conserving therapy (lumpectomy) is one of the most performed breast cancer surgeries in the United States. The best outcome of lumpectomy surgery is achieved when the surgical margins are free of cancer. When remnants of cancer are detected at the surgical margins after the initial operation, a second operation will be required to remove the cancer. Unfortunately, a significant number of patients undergo breast conserving surgery (BCS) at local hospitals that do not have access to immediate on-site pathology leading to high rates of re-excision or reoperation (greater than 30%). Therefore, there is a significant need for new intraoperative technology …

Authenticated Diagnosing Of Covid-19 Using Deep Learning-Based Ct Image Encryption Approach, Mohamed Attia Abdelgwad, Amira Hassan Abed, Mahmoud Bahloul

Future Computing and Informatics Journal

Researchers are motivated to use artificial intelligence in biometrics, medical imaging encryption, as well as cybersecurity due to its rapid progress. An encryption method for CT scans—which are used to diagnose COVID-19 disease—is proposed in this study. The suggested encryption method creates a connection among an individual's face picture and CT image to increase confidentiality. The simple CT picture is first enhanced with a host image. An encryption key is multiplied by the final result. This key is produced by applying a Convolutional Neural Network (CNN) to recognize characteristics from people's face photographs. Additionally, a straightforward CNN with three convolutional …

Segmentation And Classification Of Left Ventricular Abnormalities In Cardiac Mri Using Initial Point Prediction Based Deformable Model, Md. Asadur Rahman, Md. Al Noman, A. B. M. Aowlad Hossain

Future Computing and Informatics Journal

The shape of the left ventricle (LV) of a cardiac magnetic resonance image (CMRI) helps physicians to diagnose different cardiac abnormalities. The similarity of pixel intensity and shape of LV with neighbor tissues, the imprecision of boundaries, and the presence of noise are the challenges to accurate segmentation of LV. This paper contributes to the successful implementation of an automatic edge contouring method to segment LV area from CMRI and detect whether the ventricle belongs to abnormalities. This method proposes the regression-based artificial neural network to predict the possible initial position of the deformable edge-based active contour model for precise …

"Blockchain-Enhanced Electronic Health Records: A Secure And Immutable Approach To Ehr Management", Mostafa Abdelwahed Eltabakh, Mohamed E. Nasr, Emad Abd-Elrahman, Roayat Ismail Abdelfatah

Journal of Engineering Research

Traditional Electronic Health Record (EHR) systems face security risks, data misuse, and audit trail concerns. This paper proposes leveraging blockchain technology to improve EHRs, emphasizing Blockchain's potential to enhance data security, accessibility, and privacy through its encrypted and interconnected data block system, thereby addressing the core challenges of conventional EHR practices. This paper introduces a blockchain-based framework designed to consolidate and secure patient data within a singular record owned by the patient. Developed on the Ethereum network utilizing Ganache, this system employs programming languages and tools such as Solidity and web3.js. It leverages the blockchain platform for storing patient data …

Auxiliary Diagnosis Of Dental Calculus Based On Deep Learning And Image Enhancement By Bitewing Radiographs, Tai Jung Lin, Yen Ting Lin, Yuan Jin Lin, Ai Yun Tseng, Chien Yu Lin, Li Ting Lo, Tsung Yi Chen, Shih Lun Chen, Chiung An Chen, Kuo Chen Li, Patricia Angela R. Abu

Ateneo Laboratory for Intelligent Visual Environments

In the field of dentistry, the presence of dental calculus is a commonly encountered issue. If not addressed promptly, it has the potential to lead to gum inflammation and eventual tooth loss. Bitewing (BW) images play a crucial role by providing a comprehensive visual representation of the tooth structure, allowing dentists to examine hard-to-reach areas with precision during clinical assessments. This visual aid significantly aids in the early detection of calculus, facilitating timely interventions and improving overall outcomes for patients. This study introduces a system designed for the detection of dental calculus in BW images, leveraging the power of YOLOv8 …

A Kinematic Analysis Of The Shoulder During The Volleyball Attack Using Euler And Helical Axis Methods, Victoria Jolliff

Biomedical Engineering Theses & Dissertations

The shoulder is a complex joint with a wide range of motion, including flexion, extension, abduction, adduction, and internal and external rotation. In volleyball, repetitive overhand movements can cause shoulder overuse injuries. The primary offensive move, the attack, involves the approach, arm cocking, arm acceleration, and follow-through phases. Motion capture analysis and techniques like calculating Euler angles and rotation about a mean helical axis can evaluate shoulder movements. This study aimed to calculate shoulder movements during each phase of the volleyball attack using the Euler angle YXY sequence and the helical axis method. Different attack types, such as cross-court and …

Deep Learning Framework For Graph-Based Molecular Drug Discovery, Daniel Manu

Electrical and Computer Engineering ETDs

This dissertation proposes the GraphGANFed framework, which combines Graph Convolutional Networks (GCN), Generative Adversarial Networks (GAN), and Federated Learning (FL) to generate novel molecules while preserving data privacy. FL allows learning from distributed clients without sharing local datasets, GCN extracts molecular structural properties, and GAN generates new molecules retaining the learned properties. Extensive simulations on three benchmark datasets show GraphGANFed's effectiveness, producing molecules with high novelty (≈ 100) and diversity (> 0.9). Results indicate a trade-off among evaluation metrics, and the right dropout ratio avoids mode collapse. Additionally, Conditional GraphGANFed (cGraphGANFed) incorporates a critic network from Reinforcement Learning (RL) to …

Creative Insights Into Motion: Enhancing Human Activity Understanding With 3d Data Visualization And Annotation, Isaac Browen, Hector M. Camarillo-Abad, Franceli L. Cibrian, Trudi Di Qi

Engineering Faculty Articles and Research

This paper presents a novel 3D system for human motion analysis - Motion Data Visualization and Annotation (MoViAn). Designed to provide a comprehensive visual representation of 3D human motion data, MoViAn incorporates detailed visualization of gaze direction, hand movements, and object interactions, alongside an interactive interface for efficient data annotation. A user study involving eight participants indicates that MoViAn enables users to thoroughly explore and annotate human motion data, with System Usability Scale (SUS) results demonstrating a satisfactory usability level. The contribution of this paper lies in the development of an interactive and usable data analytics tool aimed at deepening …

Shape Memory Alloy Capsule Micropump For Drug Delivery Applications, Youssef Mohamed Kotb

Theses and Dissertations

Implantable drug delivery devices have many benefits over traditional drug administration techniques and have attracted a lot of attention in recent years. By delivering the medication directly to the tissue, they enable the use of larger localized concentrations, enhancing the efficacy of the treatment. Passive-release drug delivery systems, one of the various ways to provide medication, are great inventions. However, they cannot dispense the medication on demand since they are nonprogrammable. Therefore, active actuators are more advantageous in delivery applications. Smart material actuators, however, have greatly increased in popularity for manufacturing wearable and implantable micropumps due to their high energy …

Technologies For Wearable Seizure Detection: A Systematic Review, Rhema Losli

University Honors Theses

Knowing when a seizure occurred is helpful because this information can be used to evaluate the effectiveness of seizure interventions and possibly alert caregivers to emergency situations. The current practice for recording seizures outside of a hospital and without sensors is through keeping a self-reported seizure diary. This practice may be unreliable if the diary is not updated or the person having the seizure does not realize it is happening. Wearable seizure detectors aim to solve this problem by reliably recording when a seizure happened and either sending out an alert or storing the data for later analysis. In this …

Heartfev1: A Mobile Electrocardiogram Based System For Inferring Forced Expiratory Volume In One Second From Patients With Chronic Obstructive Pulmonary Disease, Maria Nyamukuru

Dartmouth College Ph.D Dissertations

Chronic Obstructive Pulmonary Disease (COPD), characterized by chronic airway inflammation and airflow obstruction, is the third leading cause of death globally. Patients with COPD experience exacerbated symptoms like breathlessness and cough, significantly impacting their quality of life and leading to costly hospitalizations. Early detection of COPD exacerbations is crucial for mitigating these negative effects.

The most critical element for early detection of COPD exacerbations is daily monitoring of lung function, particularly forced expiratory volume in one second (FEV1), a key metric of lung function. By tracking declines in FEV1, COPD exacerbations can be predicted up to two weeks in advance, …

2-Channel Eeg Neurofeedback System, Tim Erwin, Donna Nikjou, Sebastian Turkewitz

Electrical Engineering

This work describes the design of an EEG-based neurofeedback system which provides users with real-time feedback on their level of focus or relaxation. By analyzing the spectral content of the brain activity measured via scalp electrodes, focus and relaxation levels can be quantified. Based on these measurements, live feedback in the form of moving bar graphs is provided to users, allowing them to gain awareness of their mental-state and more efficiently learn how to consciously relax or focus. This project covers the design of the system, including amplification and filtering stages, digitization, and signal processing. The system interfaces with a …

Generative Data Augmentation: Using Dcgan To Expand Training Datasets For Chest X-Ray Pneumonia Detection, Ryan D. Maier

Master's Theses

Recent advancements in computer vision have demonstrated remarkable success in image classification tasks, particularly when provided with an ample supply of accurately labeled images for training. These techniques have also exhibited significant potential in revolutionizing computer-aided medical diagnosis by enabling the segmentation and classification of medical images, leveraging Convolutional Neural Networks (CNNs) and similar models. However, the integration of such technologies into clinical practice faces notable challenges. Chief among these is the obstacle of acquiring high-quality medical imaging data for training purposes. Patient privacy concerns often hinder researchers from accessing large datasets, while less common medical conditions pose additional hurdles …

Providing Cadence Feedback In Real-Time To Guide Cardiovascular Workouts, Levi O. Rash

Master's Theses

Cardiovascular workouts offer numerous health benefits, yet beginners often find it challenging to initiate them. Existing wearable technologies, although providing valuable feedback such as heart rate zones, often disrupt the workout flow and distract users due to the need for interaction with the wearable display. In response, we propose an alternative feedback mechanism: cadence, measured in steps per minute. This feedback mechanism uses multiplicative control to produce the correct cadence for the user’s target heart rate (HR). To model the HR and cadence relationship, a first-order system was used. The prototype implementation of this system was completed in Arduino, using …

3d Automated Surgeon’S Hand Motion Assessment Using A Cascade Fuzzy Supervisor During Intelligent Box-Trainer System Skills Training In A Multi-Thread Video Processing, Fatemeh Rashidi Fathabadi

Dissertations

For certain surgical procedures, Minimally Invasive Surgery (MIS) has become more advantageous than traditional open surgery. Therefore, mastery of laparoscopic skills is an essential component of surgical training and requires considerable time and effort. The Fundamentals of Laparoscopic Surgery (FLS) program has been developed as a tool to improve and assess fundamental surgical skills. In fact, using a low-cost Box-Trainer or a simulator, laparoscopic surgeons are required to train using a set of structured tasks that can be objectively used to assess their laparoscopic skills, which must be mastered before carrying out real-life laparoscopic procedures. These tasks include peg transfer, …

Affordable Bioprint Head-Adapter For 3d Printers, Andrew Ceralde, Dominic Drake, Noah Engles, Mohammad Alwan, Nevada Perry

Honors Capstones

Introduction: Addressing the need for affordable and accessible bioprinting technology, the Northern Illinois University bioprinting research and design project aims to democratize the field by developing an open source bioprint head. The initiative targets the prohibitive cost of commercial bioprinters by proposing an optimal design that can be integrated with widely available 3D printers, like the Creality Ender-3. This approach seeks to enable the widespread adoption of bioprinting technology, particularly for applications in tissue engineering and regenerative medicine.

Methods: Leveraging SolidWorks for design, the project employs a methodology that combines a precision extrusion system with thermal and UV crosslinking capabilities. …