Biomedical Engineering and Bioengineering Commons^™

A Protein-Based Therapeutic Combination For The Treatment Of Hard-To-Heal Wounds, Graham L. Strauss

USF Tampa Graduate Theses and Dissertations

Chronic wounds present many clinical challenges in relation to the successful treatment and closure of the damaged tissue. Most current treatment methods focused on one or two aspects to drive wound closure, while most chronic wounds are multifactorial environments with many of those dependencies relying on the termination of one another to effectively gain tissue construction, closure, and full skin thickness and composition. Natural wound healing processes allude to potential biologics that can impede the chronic breakdown of tissue, while restoring deposition of new tissue, and effectively leading to a healed wound. Proteases secreted by the body’s immune system lay …

Automated Wound Segmentation And Dimension Measurement Using Rgb-D Image, Chih-Yun Pai

USF Tampa Graduate Theses and Dissertations

Accurate pressure ulcer (PrU) measurement is critical in assessing the effectiveness of PrU treatment. The traditional measurement process is manual, subjective, and requires frequent contact with the wound. The manual measurement relies on human observation which makes the measurement inconsistent, and the frequent contact with the wound increases risk of contamination or infection. The purpose of this research was to develop an automatic Pressure Ulcer Monitoring System (PrUMS) using a depth camera to provide automated, non-contact wound measurement. In this dissertation, 1) a wound segmentation with traditional machine learning method, which combines the color classification using K-Nearest Neighbors and the …

An Automated Framework For Connected Speech Evaluation Of Neurodegenerative Disease: A Case Study In Parkinson's Disease, Sai Bharadwaj Appakaya

USF Tampa Graduate Theses and Dissertations

Neurodegenerative diseases affect millions of people around the world. The progressive degeneration worsens the symptoms, heavily impacting the quality of life of the patients as well as the caregivers. Speech production is one of the physiological processes affected by neurodegenerative diseases like Alzheimer’s disease, amyotrophic lateral sclerosis (ALS) and Parkinson’s disease (PD). Speech is the most basic form of communication, and the effect of neurodegeneration degrades speech production, thereby reducing social interaction and mental well-being. PD is the second most common neurodegenerative disease affecting speech production in 90% of the diagnosed individuals. Speech analysis methods for PD in clinical methods …

An Investigation Of Cross-Links On Crystallization And Degradation In A Novel, Photocross-Linkable Poly (Lactic Acid) System, Nicholas Baksh

USF Tampa Graduate Theses and Dissertations

Polymeric molecular structure consists of repeating units bonded together. Mechanicalproperties can be altered without affecting chemical makeup by altering the number of these units. Small molecules can be introduced and/or polymers can be modified to form bonds between molecular chains. Cross-linking, as this is called, also introduces mechanical variation with minimal effects on chemical composition. Lastly, polymer chains reorient themselves in response to intermolecular forces. This temperature dependent response is known as crystallization. Although chemistry is unaltered, mechanical properties can depend highly on the percent of the sample that is crystallized.

Cross-linking is known to enhance the mechanical properties of …

Active Deep Learning Method To Automate Unbiased Stereology Cell Counting, Saeed Alahmari

USF Tampa Graduate Theses and Dissertations

Cell quantification in histopathology images plays a significant role in understanding and diagnosing diseases such as cancer and Alzheimers. The gold-standard for quantifying cells in tissue sections is the unbiased stereology approach. Unfortunately, in unbiased stereology current practices rely on a well-trained human to manually count hundreds of cells in microscopy images. However, this human-based manual approach is time-consuming, labor-intensive, subject to human errors, recognition bias, fatigue, variable training, poor reproducibility, and inter-observer error. Thus, the lack of high-throughput technology for automating unbiased stereology analyses remains a major obstacle to further progress in a wide range of neuroscience and cancer …

Lung Nodule Malignancy Prediction From Computed Tomography Images Using Deep Learning, Rahul Paul

USF Tampa Graduate Theses and Dissertations

Lung cancer has a high incidence and mortality rate. The five-year relative survival rate for all lung cancers is 18%. Due to the high mortality and incidence rate of lung cancer worldwide, early detection is essential. Low dose Computed Tomography (CT) is a commonly used technique for screening, diagnosis, and prognosis of non-small cell lung cancer (NSCLC). The National Lung Screening Trial (NLST) compared low-dose helical computed tomography (LDCT) and standard chest radiography (CXR) for three annual screens and reported a 20% relative reduction in lung cancer mortality for LDCT compared to CXR. As such, LDCT screening for lung cancer …

Statistical Learning Of Biomedical Non-Stationary Signals And Quality Of Life Modeling, Mahdi Goudarzi

USF Tampa Graduate Theses and Dissertations

Statistical learning is a set of tools for modeling and understanding complex datasets. It is a recently developed area in statistics and blends with parallel developments in computer science and, in particular, machine learning.

The classification of biomedical non-stationary signals such as Electroencephalogram (EEG) is always a challenging problem due to their complexity. The low spatial resolution on the scalp, curse of dimensionality, poor signal-to-noise ratio are disadvantages of working with biomedical signals. EEG signals are unstructured data which needs preprocessing steps to extract informative features which are measurable and predictive. In the first two chapters of this dissertation, EEG …

Characterization Of Computed Tomography Radiomic Features Using Texture Phantoms, Muhammad Shafiq Ul Hassan

USF Tampa Graduate Theses and Dissertations

Radiomics treats images as quantitative data and promises to improve cancer prediction in radiology and therapy response assessment in radiation oncology. However, there are a number of fundamental problems that need to be solved in order to potentially apply radiomic features in clinic. The first basic step in computed tomography (CT) radiomic analysis is the acquisition of images using selectable image acquisition and reconstruction parameters. Radiomic features have shown large variability due to variation of these parameters. Therefore, it is important to develop methods to address these variability issues in radiomic features due to each CT parameter. To this end, …

Elastin-Like Polypeptide Fusion Tag As A Protein-Dependent Solubility Enhancer Of Cysteine-Knot Growth Factors, Tamina L. Johnson

USF Tampa Graduate Theses and Dissertations

Elastin-like peptide (ELP) fusions promote therapeutic delivery and efficacy. Recombinant proteins, like neurotrophins, lack bioavailability, have short in vivo half-lives, and require high manufacturing costs. Fusing recombinant proteins with genetically encodable ELPs will increase bioavailability, enhance in vivo solubilization, as well as provide a cost-effective method for purification without the need for chromatography. During expression of neurotrophin-ELP (N-ELP) fusions, dense water-insoluble aggregates known as inclusion bodies (IBs) are formed. Inclusion bodies are partially and misfolded proteins that usually require denaturants like Urea for solubilization. Strong denaturants arrest ELPs stimuli-responsive property and increase unwanted aggregation, making purification difficult, yet possible. The …

Nano-Photonic Waveguides For Chemical And Biomedical Sensing, Surya Venkatasekhar Cheemalapati

USF Tampa Graduate Theses and Dissertations

In this dissertation, advances in the fields of Photonics, and Plasmonics, and specifically, single cell analysis and waveguide sensing will be addressed. The first part of the dissertation is on Finite Difference Time Domain (FDTD) optimization and experimental demonstration of a nano-scale instrument that allows sensing at the cellular and subcellular levels. A new design of plasmonic coupler into a nanoscale waveguide is proposed and optimized using FDTD simulations. Following this, a subcellular nanoendoscope that can locally excite fluorescence in labelled cell organelles and collect the emitted fluorescent light for detailed spectrum analysis is fabricated and tested. The nanoendoscope has …

Increasing 18f-Fdg Pet/Ct Capabilities In Radiotherapy For Lung And Esophageal Cancer Via Image Feature Analysis, Jasmine Alexandria Oliver

USF Tampa Graduate Theses and Dissertations

Positron Emission Tomography (PET) is an imaging modality that has become increasingly beneficial in Radiotherapy by improving treatment planning (1). PET reveals tumor volumes that are not well visualized on computed tomography CT or MRI, recognizes metastatic disease, and assesses radiotherapy treatment (1). It also reveals areas of the tumor that are more radiosensitive allowing for dose painting - a non-homogenous dose treatment across the tumor (1). However, PET is not without limitations. The quantitative unit of PET images, the Standardized Uptake Value (SUV), is affected by many factors such as reconstruction algorithm, patient weight, and tracer uptake time (2). …

Fabrication Of Tissue Precursors Induced By Shape-Changing Hydrogels, Olukemi O. Akintewe

USF Tampa Graduate Theses and Dissertations

Scaffold based tissue reconstruction inherently limits regenerative capacity due to inflammatory response and limited cell migration. In contrast, scaffold-free methods promise formation of functional tissues with both reduced adverse host reactions and enhanced integration. Cell-sheet engineering is a well-known bottom-up tissue engineering approach that allows the release of intact cell sheet from a temperature responsive polymer such as poly-N-isopropylacrylamide (pNIPAAm). pNIPAAm is an ideal template for culturing cell sheets because it undergoes a sharp volume-phase transition owing to the hydrophilic and hydrophobic interaction around its lower critical solution temperature (LCST) of 32°C, a temperature close to physiological temperature. Compared to …

Heterogeneous Modeling Of Medical Image Data Using B-Spline Functions, Olya Grove

USF Tampa Graduate Theses and Dissertations

Ongoing developments in the field of medical imaging modalities have pushed the frontiers of modern medicine and biomedical engineering, prompting the need for new applications to improve diagnosis, treatment and prevention of diseases.

Biomedical data visualization and modeling rely predominately on manual processing and utilization of voxel and facet based homogeneous models. Biological structures are naturally heterogeneous and in order to accurately design and biomimic biological structures, properties such as chemical composition, size and shape of biological constituents need to be incorporated in the computational biological models.

Our proposed approach involves generating a density point cloud based on the intensity …

Biological Effective Dose (Bed) Distribution Matching For Obtaining Brachytherapy Prescription Doses & Dosimetric Optimization For Hybrid Seed Brachytherapy, Jakub Pritz

USF Tampa Graduate Theses and Dissertations

Radioactive seed implant brachytherapy is a common radiotherapy treatment method for prostate cancer. In current clinical practice, a seed consists of a single isotope, such as ¹²⁵I or ¹⁰³Pd. A seed containing a mixture of two isotopes has been proposed for prostate cancer treatment. This study investigates a method for defining a prescription dose for new seed compositions based on matching the biological equivalent dose (BED) of a reference plan.

Ten prostate cancer cases previously treated using single isotope seeds (5 using ¹²⁵I seeds and 5 using ¹⁰³Pd seeds) were selected for this study. Verification of …

A Novel Device For Cell-Cell Electrofusion, Justin T. Stewart

USF Tampa Graduate Theses and Dissertations

Cell transplantation therapy is a potentially powerful tool and can be used to replace defective cells with healthy cells. This offers the possibility of alleviating the destructive symptoms for many diseases such as Parkinson's disease, Alzheimer's disease, stroke, spinal cord trauma, Type I diabetes and many more. While there are many diseases that could be positively impacted from cell transplantation therapy, the focus of this research is insulin dependent, Type I Diabetes.

The Islets of Langerhans are composed of various types of cells located in the pancreas and are responsible for a variety of biochemical functions. Specifically, the beta Islet …