Biomedical Engineering and Bioengineering Commons^™

Examining Metal Contents In Primary And Secondhand Aerosols Released By Electronic Cigarettes, Kashala Fabrice Kapiamba, Weixing Hao, Stephen Adom, Wenyan Liu, Yue-Wern Huang, Yang Wang

Chemistry Faculty Research & Creative Works

The usage of electronic cigarettes (ECs) has surged since their invention two decades ago. However, to date, the health effects of EC aerosol exposure are still not well understood because of insufficient data on the chemical composition of EC aerosols and the corresponding evidence of health risks upon exposure. Herein, we quantified the metals in primary and secondhand aerosols generated by three brands of ECs. By combining aerosol filter sampling and inductively coupled plasma mass spectrometry (ICP-MS), we assessed the mass of metals as a function of EC flavoring, nicotine concentration, device power, puff duration, and aging of the devices. …

Deep Learning For Digitized Histology Image Analysis, Sudhir Sornapudi

Doctoral Dissertations

“Cervical cancer is the fourth most frequent cancer that affects women worldwide. Assessment of cervical intraepithelial neoplasia (CIN) through histopathology remains as the standard for absolute determination of cancer. The examination of tissue samples under a microscope requires considerable time and effort from expert pathologists. There is a need to design an automated tool to assist pathologists for digitized histology slide analysis. Pre-cervical cancer is generally determined by examining the CIN which is the growth of atypical cells from the basement membrane (bottom) to the top of the epithelium. It has four grades, including: Normal, CIN1, CIN2, and CIN3. In …

Applications Of Machine Learning In Nuclear Imaging And Radiation Detection, Shaikat Mahmood Galib

Doctoral Dissertations

"The main focus of this work is to use machine learning and data mining techniques to address some challenging problems that arise from nuclear data. Specifically, two problem areas are discussed: nuclear imaging and radiation detection. The techniques to approach these problems are primarily based on a variant of Artificial Neural Network (ANN) called Convolutional Neural Network (CNN), which is one of the most popular forms of 'deep learning' technique.

The first problem is about interpreting and analyzing 3D medical radiation images automatically. A method is developed to identify and quantify deformable image registration (DIR) errors from lung CT scans …

The Viability Of Advantg Deterministic Method For Synthetic Radiography Generation, Andrew Albert Bingham

Masters Theses

"Time sensitive and high resolution image simulations are needed for synthetic radiography generation. The standard stochastic approach requires lengthy run times with poor statistics at higher resolutions. The investigation of the viability of a deterministic approach to synthetic radiography image generation was explored. The aim was to analyze a computational time decrease over the stochastic method. ADVANTG was compared to MCNP in multiple scenarios including a Benchtop CT prototype, to simulate high resolution radiography images. By using ADVANTG deterministic code to simulate radiography images the computational time was found to decrease over 10 times compared to the MCNP stochastic approach"--Abstract, …

Bioactivity/Cytotoxicity Of Micro-/Nano-Materials And Novel Development Of Fiber-Optic Probes For Single Cell Monitoring, Qingbo Yang

Doctoral Dissertations

"Manufactured nano-/micro-materials (MNMs) have been widely used and their interactions with niche biological environment are highly concerned for both of their biohazardous and bioactive effects, whereas no available comprehensive evaluations or regulations have been provided yet. This dissertation thus focuses on three major aspects: 1) fundamental toxicity understandings of a typical MNMs (zinc oxide nanoparticles), 2) bioactivity evaluations of representative bioactive MNMs, and 3) development of novel micro-probes for high spatial resolution monitoring. Firstly, the NP's concentration, irradiation, hydrodynamic size, and the localized pH, ionic strength, NP zeta-potential as well as dissolved oxygen levels were found correlated with the production …

Detecting, Segmenting And Tracking Bio-Medical Objects, Mingzhong Li

Doctoral Dissertations

"Studying the behavior patterns of biomedical objects helps scientists understand the underlying mechanisms. With computer vision techniques, automated monitoring can be implemented for efficient and effective analysis in biomedical studies. Promising applications have been carried out in various research topics, including insect group monitoring, malignant cell detection and segmentation, human organ segmentation and nano-particle tracking.

In general, applications of computer vision techniques in monitoring biomedical objects include the following stages: detection, segmentation and tracking. Challenges in each stage will potentially lead to unsatisfactory results of automated monitoring. These challenges include different foreground-background contrast, fast motion blur, clutter, object overlap and …

In Vitro Study Of Wound-Healing Capabilities Of Bioactive Glass Fibers Under Various Culture Conditions, Sisi Chen

Masters Theses

"Bioactive borate glass has been recognized to have both hard and soft tissue repair and regeneration capabilities through stimulating both osteogenesis and angiogenesis. However, the underlying physiological and cellular mechanism behind this function remains unclear. In this study, in vitro dynamic flow modules were designed to mimic the micro-environment near the vascular depletion and hyperplasia area in wound-healing regions, and were used to investigate the biocompatibility and functionality of borate glass nano-/micro-fibers. Glass-cell interactions were investigated either by dosing fibers to the upstream of or co-cultured with cells, and two types of borate glasses (with or without CuO/ZnO doped were …

Cervical Cancer Histology Image Feature Extraction And Classification, Peng Guo

Masters Theses

"Cervical cancer, the second most common cancer affecting women worldwide and the most common in developing countries can be cured if detected early and treated. Expert pathologists routinely visually examine histology slides for cervix tissue abnormality assessment. In previous research, an automated, localized, fusion-based approach was investigated for classifying squamous epithelium into Normal, CIN1, CIN2, and CIN3 grades of cervical intraepithelial neoplasia (CIN) based on image analysis of 62 digitized histology images obtained through the National Library of Medicine. In this research, CIN grade assessments from two pathologists are analyzed and are used to facilitate atypical cell concentration feature development …