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Development Of A Multispectral Vis-Swir Imaging Modality For Cutaneous Water Assessment, Quinlan McGrath 2023 Washington University in St. Louis

Development Of A Multispectral Vis-Swir Imaging Modality For Cutaneous Water Assessment, Quinlan Mcgrath

McKelvey School of Engineering Graduate Student Theses & Dissertations

Inflammatory skin diseases are estimated to impact 20% of the global population and are the fourth leading cause of nonfatal disability worldwide. Diagnosis and management are predominantly based on clinician visual assessment of disease related changes in skin morphology. The qualitative nature of this method can result in misdiagnosis and underdiagnoses of treatable diseases. There persists systematic undertreatment of skin of color patients given the more subtle presentation of erythema against pigmented skin. There exists a clinical need for a quantitative and objective inflammation assessment tool that meets the needs of a diverse patient population. The accumulation of interstitial fluid …


A Comparison Of Optical Measurement Methods For The Growth Of S. Cerevisiae, Jackson Black 2023 University of Arkansas, Fayetteville

A Comparison Of Optical Measurement Methods For The Growth Of S. Cerevisiae, Jackson Black

Chemical Engineering Undergraduate Honors Theses

Genetic engineering of living organisms provides the opportunity to express and harvest different proteins from cell surfaces. Yeast (S. cerevisiae) is one such organism and is capable of being grown on an industrial scale. Cellular concentration is an important parameter to monitor while fermentation processes are underway, in order to control the environment inside the growth medium and maximize yields. Spectrophotometry is a conventional method for measuring concentration, but is limited by a narrow absorbance range, and the need for on-site periodic sampling. A continuous method of measurement, as provided by Bug Labs BE2100 non-invasive biomass monitor, would …


Light Sheet Microscopy Incubation Design And Control Scheme, Venkatanathan Kidambi 2023 University of Connecticut

Light Sheet Microscopy Incubation Design And Control Scheme, Venkatanathan Kidambi

Honors Scholar Theses

The focus of the following paper is the development of a light sheet or selective plane illumination microscopy (LSM / SPIM) platform to support long duration three dimensional imaging of various cells and tissues. This paper describes the complete design and fabrication process behind the prototype, including a definition of light sheet microscopy and its differences from confocal microscopy, as well as existing open source selective plane microscopy literature and designs. The complete engineering design process as applied to the microscope design is described in detail. Specifically, this paper will focus on the development of an incubation chamber for light …


Automated Segmentation Of Autofluorescence Lifetime Images Using A Convolutional Neural Network, Nicole Hooten 2023 University of Arkansas, Fayetteville

Automated Segmentation Of Autofluorescence Lifetime Images Using A Convolutional Neural Network, Nicole Hooten

Biomedical Engineering Undergraduate Honors Theses

Chronic wounds affect nearly 1 out of every 50 people in the United States, decreasing quality of life and putting people with potential comorbidities at high risk for obtaining an infection. Wound healing progress in clinical settings is measured by tracking wound size and there are currently no non-invasive, quantitative measurement techniques. Previous studies have proposed nicotinamide adenine dinucleotide (NADH) autofluorescence lifetime (FLIM) imaging of the wound edge as a method to quantify the wound healing process by connecting the role of NADH in cellular metabolism to wound healing stage. However, evaluation of FLIM images is heavily subjective, as a …


Correlation Of Intracellular Metabolites With Optical Metabolic Imaging In Polarized Macrophages As Indicators Of Metabolic Reprogramming, Abby Claire Denison, Shelby Bess 2023 University of Arkansas, Fayetteville

Correlation Of Intracellular Metabolites With Optical Metabolic Imaging In Polarized Macrophages As Indicators Of Metabolic Reprogramming, Abby Claire Denison, Shelby Bess

Biomedical Engineering Undergraduate Honors Theses

Macrophages are a type of immune cell that are characterized by their ability to differentiate into various active phenotypes based on environmental stimuli. They can generally be classified as one of two extremes: inflammatory/M1 or wound-healing/M2. Macrophage populations in vivo, however, are rarely homogenous, and since macrophages play vital roles in the immune response, particularly in the context of the tumor microenvironment (TME), it’s important to be able to investigate and understand heterogenous macrophage populations to develop more effective treatments. Recently, autofluorescence imaging such as multiphoton microscopy and fluorescence lifetime imaging microscopy (FLIM) of metabolic cofactors NADH and FAD have …


Synthesis, Radiolabeling And Evaluation Of A Suite Of Tracers With 44Sc For Detecting Extracellular Dna, Zhiyao Li 2023 Washington University in St. Louis

Synthesis, Radiolabeling And Evaluation Of A Suite Of Tracers With 44Sc For Detecting Extracellular Dna, Zhiyao Li

McKelvey School of Engineering Graduate Student Theses & Dissertations

Neutrophil extracellular traps involve the rapid translocation of DNA to the outside of the cell under certain stimuli. This structure forms a fibrous network that is able to limit the spread of pathogens and to kill microorganisms. It has also been shown to be present in various pathological processes such as inflammation, autoimmune diseases, and cancer metastasis. Currently, the formation process of NETs in vivo is being extensively studied. However noninvasive detection and quantitation has yet to be achieved. A class of PET tracers are described here that consists of a DNA dye as the backbone that is labeled with …


Portable Diffuse Reflectance Spectroscopy For Non-Invasive And Quantitative Assessment Of The Parathyroid Glands Viability During Surgery, Mark Romine, Linh Luong, Alex Moazzen, Katie Cho, Paul Lee 2023 Kennesaw State University

Portable Diffuse Reflectance Spectroscopy For Non-Invasive And Quantitative Assessment Of The Parathyroid Glands Viability During Surgery, Mark Romine, Linh Luong, Alex Moazzen, Katie Cho, Paul Lee

Symposium of Student Scholars

Portable Diffuse Reflectance Spectroscopy for Non-invasive and Quantitative Assessment of the Parathyroid Glands Viability During Surgery

Mark Romine, Linh Luong, Alex Moazzen, Katie Cho and Paul Lee

The parathyroid glands (PTGs) are responsible for the regulation of calcium levels in the blood by secreting a parathyroid hormone. This parathyroid hormone then regulates the body’s absorption, storage, and secretion of calcium, which can directly affect the way muscles and nerves operate. PTGs are often at risk of damage, or accidental removal during thyroid surgeries, because it is challenging to identify PTGs and to determine their viability. Current methods of visual inspections …


Wireless, Handheld Diffuse Reflectance Spectroscopy To Quantify Tissue Microvascular Hemodynamics, Linh Luong, Alex Moazzen, Mark Romine, Katie Cho, Paul Lee 2023 Kennesaw State University

Wireless, Handheld Diffuse Reflectance Spectroscopy To Quantify Tissue Microvascular Hemodynamics, Linh Luong, Alex Moazzen, Mark Romine, Katie Cho, Paul Lee

Symposium of Student Scholars

Diffuse Reflectance Spectroscopy (DRS) is a non-invasive optical method to characterize tissue optical properties for disease diagnosis and health monitoring. Two optical fibers are often used in a DRS system: one to deliver light to the tissue and the other to gather diffuse reflectance spectra, which provide quantitative details about the structure and composition of the tissue. The conventional DRS system, however, is expensive, bulky, and composed of fragile optical fibers and multiple electrical connections. Here we propose to build a wireless, handheld, and fiber-less diffuse optical spectroscopy system. Unfortunately, the diffusion approximation utilized for data analysis of the conventional …


Enhancement Of Deep Learning Protein Structure Prediction, Ruoming Shen 2023 Ocean Lakes High School

Enhancement Of Deep Learning Protein Structure Prediction, Ruoming Shen

Modeling, Simulation and Visualization Student Capstone Conference

Protein modeling is a rapidly expanding field with valuable applications in the pharmaceutical industry. Accurate protein structure prediction facilitates drug design, as extensive knowledge about the atomic structure of a given protein enables scientists to target that protein in the human body. However, protein structure identification in certain types of protein images remains challenging, with medium resolution cryogenic electron microscopy (cryo-EM) protein density maps particularly difficult to analyze. Recent advancements in computational methods, namely deep learning, have improved protein modeling. To maximize its accuracy, a deep learning model requires copious amounts of up-to-date training data.

This project explores DeepSSETracer, a …


Image Analysis Methodology For Evaluating Coating Uniformity Of Drug-Coated Angioplasty Balloons, Allison Dobson Zieschang 2023 Louisiana State University and Agricultural and Mechanical College

Image Analysis Methodology For Evaluating Coating Uniformity Of Drug-Coated Angioplasty Balloons, Allison Dobson Zieschang

LSU Master's Theses

Percutaneous transluminal balloon angioplasty (PTA) is a surgical procedure to treat peripheral artery disease, but restenosis causes suboptimal outcomes in many patients. Drug-coated angioplasty balloons (DCBs) were developed to reduce the risk of restenosis by delivering anti-proliferative drugs to the lesion. The efficacy of DCBs depends on factors like drug loading and drug release rate, both of which are directly impacted by the coating uniformity. This thesis evaluates the uniformity of DBCs using fluorescence microscopy, scanning electron microscopy (SEM), qualitative analysis, and an image processing algorithm. Uniformity was quantified by three measurements: histogram standard deviation, histogram percentage of coverage, and …


Computational Design Of Fiber-Optic Probes For Biosensing, Suwarna Karna 2023 University of Texas at Tyler

Computational Design Of Fiber-Optic Probes For Biosensing, Suwarna Karna

Electrical Engineering Theses

This thesis presents a study on the optical characteristics of hollow-core photonic crystal fibers (HC-PCFs) with a band gap cladding structure and their applications in optical fiber sensing. This 800B HC-PCF exhibited excellent optical properties and has a flexible structure, which makes them suitable for a wide range of industrial applications. Finite element simulations and structural optimization designs were conducted using the surface plasmon resonance (SPR) technique to determine the optimal performance parameters of the 800B HC-PCF. The fiber was further modified using the SPR technique to improve its practical detection capabilities. The performance of the modified fiber was observed …


A Device For Measuring Acoustic Output Intensity Of Transcranial Doppler Ultrasound Transducers For Comparison With Fda Regulations, Sarah Altman, Gregory Bashford, Benjamin Hage 2023 University of Nebraska-Lincoln

A Device For Measuring Acoustic Output Intensity Of Transcranial Doppler Ultrasound Transducers For Comparison With Fda Regulations, Sarah Altman, Gregory Bashford, Benjamin Hage

Honors Program: Senior Projects (Public)

Transcranial Doppler Ultrasonography (TCD) is a non-invasive methodology which can evaluate cerebral blood flow velocity in real time. Single-element focused circular transducers placed on the scalp produce ultrasound waves capable of penetrating the skull with minimal aberration, enabling measurement of the Doppler shift. As such, TCD can measure blood flow velocity in the internal carotid and vertebral arteries, as well as the arteries of the Circle of Willis: the Anterior Cerebral (ACA), Posterior Cerebral (PCA), and Middle Cerebral Arteries (MCA). Intracranial aneurysm and ischemic stroke are serious conditions in which ballooning or occlusion of cerebral vessels cause insufficient perfusion, leading …


Differentiating Axonal From Demyelinating Neuropathies Using Multiparametric Quantitative Mri Of Peripheral Nerves, Jacob D. Baraz, Stephanie Xuan, Sadaf Saba, Xue Yang, Ryan Castoro, Yang Xuan, Alison Roth, Richard D. Dortch, Jun Li, Yongsheng Chen 2023 Wayne State University School of Medicine

Differentiating Axonal From Demyelinating Neuropathies Using Multiparametric Quantitative Mri Of Peripheral Nerves, Jacob D. Baraz, Stephanie Xuan, Sadaf Saba, Xue Yang, Ryan Castoro, Yang Xuan, Alison Roth, Richard D. Dortch, Jun Li, Yongsheng Chen

Medical Student Research Symposium

Objectives: To develop a multiparametric quantitative MRI (qMRI) method to track pathological changes in the peripheral neuropathies.

Background: Irrespective of the causes or types of polyneuropathies, peripheral nerves are mainly afflicted by two kinds of pathologies – axonal loss and demyelination. It is critical to differentiate between the two as treatments are different for the two conditions. While nerve conduction studies (NCS) have been used to differentiate the two pathologies in the distal nerves, there are no tools to probe the pathologies in the proximal peripheral nerves. This is particularly needed when distal nerves become non-responsive in NCS.

Methods: We …


Efficient Scopeformer: Towards Scalable And Rich Feature Extraction For Intracranial Hemorrhage Detection Using Hybrid Convolution And Vision Transformer Networks, Yassine Barhoumi 2023 Rowan University

Efficient Scopeformer: Towards Scalable And Rich Feature Extraction For Intracranial Hemorrhage Detection Using Hybrid Convolution And Vision Transformer Networks, Yassine Barhoumi

Theses and Dissertations

The field of medical imaging has seen significant advancements through the use of artificial intelligence (AI) techniques. The success of deep learning models in this area has led to the need for further research. This study aims to explore the use of various deep learning algorithms and emerging modeling techniques to improve training paradigms in medical imaging. Convolutional neural networks (CNNs) are the go-to architecture for computer vision problems, but they have limitations in mapping long-term dependencies within images. To address these limitations, the study explores the use of techniques such as global average pooling and self-attention mechanisms. Additionally, the …


Deutj: An Imagej Plugin For Improved Automatic Masking And Segmentation Of Images From Confocal Microscopy, Sunny Cui 2023 Dartmouth College

Deutj: An Imagej Plugin For Improved Automatic Masking And Segmentation Of Images From Confocal Microscopy, Sunny Cui

Independent Student Projects and Publications

Due to advances in microscopic imaging, there are a plethora of biological molecules that can now be tagged and subsequentially imaged from almost any cell, organism, or tissue. However, the ability of software to analyze these images remains to be a challenge. ImageJ is open source software that allows for the processing of these images, but faces challenges when dealing with images that show weak contrast between objects of interest and background. DeutJ is an ImageJ plugin that color corrects and brightness corrects gradients that inhibit segmentation in confocal microscopy images. It can analyze hundreds of images from a given …


Session 12: Active Learning To Minimize The Possible Risk From Future Epidemics, KC Santosh 2023 University of South Dakota

Session 12: Active Learning To Minimize The Possible Risk From Future Epidemics, Kc Santosh

SDSU Data Science Symposium

In medical imaging informatics, for any future epidemics (e.g., Covid-19), deep learning (DL) models are of no use as they require a large dataset as they take months and even years to collect enough data (with annotations). In such a context, active learning (or human/expert-in-the-loop) is the must, where a machine can learn from the first day with minimum possible labeled data. In unsupervised learning, we propose to build pre-trained DL models that iteratively learn independently over time, where human/expert intervenes only when it makes mistakes and for only a limited data. In our work, deep features are used to …


Estimation Of Free Water-Corrected Microscopic Fractional Anisotropy., Nico J J Arezza, Tales Santini, Mohammad Omer, Corey A Baron 2023 Western University

Estimation Of Free Water-Corrected Microscopic Fractional Anisotropy., Nico J J Arezza, Tales Santini, Mohammad Omer, Corey A Baron

Medical Biophysics Publications

Water diffusion anisotropy MRI is sensitive to microstructural changes in the brain that are hallmarks of various neurological conditions. However, conventional metrics like fractional anisotropy are confounded by neuron fiber orientation dispersion, and the relatively low resolution of diffusion-weighted MRI gives rise to significant free water partial volume effects in many brain regions that are adjacent to cerebrospinal fluid. Microscopic fractional anisotropy is a recent metric that can report water diffusion anisotropy independent of neuron fiber orientation dispersion but is still susceptible to free water contamination. In this paper, we present a free water elimination (FWE) technique to estimate microscopic …


Dataset For Manuscript: Comparing Performance Of Spectral Image Analysis Approaches For Detection Of Cellular Signals In Time-Lapse Hyperspectral Imaging Fluorescence Excitation-Scanning Microscopy, Silas J. Leavesley 2023 University of South Alabama

Dataset For Manuscript: Comparing Performance Of Spectral Image Analysis Approaches For Detection Of Cellular Signals In Time-Lapse Hyperspectral Imaging Fluorescence Excitation-Scanning Microscopy, Silas J. Leavesley

BioImaging and BioSystems Research

The dataset contains raw and processed hyperspectral timelapse image data that are described in the manuscript:

Parker, M., Annamdevula, N. S., Pleshinger, D., Ijaz, Z., Jalkh, J., Penn, R., Deshpande, D., Rich, T. C. & Leavesley, S. J. Comparing Performance of Spectral Image Analysis Approaches for Detection of Cellular Signals in Time-Lapse Hyperspectral Imaging Fluorescence Excitation-Scanning Microscopy. Bioengineering 10, 642 (2023).


Patient-Specific Analysis Of Aortic Hemodynamics And Wall Shear Stresses In Patients Undergoing Pediatric Bariatric Surgery Using 2d Phase-Contrast Mri, Oluwaferanmi S. Akande, Joao Soares, Nathan Hargan, Dr. Uyen Truong, Haeung Kang, David Lanning 2023 Virginia Commonwealth University

Patient-Specific Analysis Of Aortic Hemodynamics And Wall Shear Stresses In Patients Undergoing Pediatric Bariatric Surgery Using 2d Phase-Contrast Mri, Oluwaferanmi S. Akande, Joao Soares, Nathan Hargan, Dr. Uyen Truong, Haeung Kang, David Lanning

UROP Posters

Patient-Specific Analysis of Aortic Hemodynamics and Wall Shear Stresses in Patients Undergoing Pediatric Bariatric Surgery using 2D Phase-Contrast MRI

Feranmi Akande1 Nathan Hargan2 Haesung Kang3 David Lanning3 Uyen Truong4 João S. Soares1

1 Department of Biomedical Engineering, College of Engineering, Virginia Commonwealth University

2 Department of Mechanical & Nuclear Engineering, College of Engineering, Virginia Commonwealth University

3 Department of Cardiology, Children’s Hospital of Richmond, Virginia Commonwealth University

Introduction: Severe obesity among today’s youth is a rising epidemic within the United States. Emerging research has linked childhood obesity with shortened life expectancy and early …


Multiscale And Multimodality Optical Imaging Of Brain Hemodynamics And Function, Mehrana Mohtasebi 2023 University of Kentucky

Multiscale And Multimodality Optical Imaging Of Brain Hemodynamics And Function, Mehrana Mohtasebi

Theses and Dissertations--Biomedical Engineering

Frequent measurement of cerebral hemodynamics is crucial for continuous assessment of brain function and health. Low-frequency oscillations (LFOs; < 0.1 Hz) have shown promise as an indicator of altered neurologic activity in the abnormal brain. Moreover, quantification of temporal correlations in LFOs across distinct brain regions enables mapping of regional neurovascular disorders. Portable diffuse optical techniques such as near-infrared spectroscopy (NIRS) and diffuse correlation spectroscopy (DCS) enable noninvasive and continuous measurements of cerebral oxygenation and cerebral blood flow (CBF), respectively. However, most NIRS/DCS systems use limited numbers of discrete light sources and detectors and thus lack combinations of high temporal/spatial resolution and large field-of-view (FOV) for brain imaging. Recent development of an innovative noncontact speckle contrast diffuse correlation tomography (scDCT) in our lab provides a low-cost and portable tool for high-density imaging of CBF distributions over large FOVs. The scDCT uses a galvo-mirror to remotely deliver coherent point near-infrared light to multiple source positions and a CMOS camera as a high-density 2-D detector array to quantify spatial fluctuations of diffuse laser speckles, resulting from movement of red blood cells. Boundary CBF data were input to a unique finite-element-method (FEM)-based reconstruction algorithm for 3-D imaging of CBF distributions. However, scDCT was hindered for extracting LFOs due to its low sampling rate. In this study, scDCT was optimized to achieve high sampling rates and fast image reconstructions by use of moving window algorithms with parallel computations (Project 1). Power spectral density (PSD) analysis was performed to investigate altered LFOs during transient cerebral ischemia in neonatal piglets. Transient cerebral ischemia caused reductions in both CBF and PSD, supporting inclusion of scDCT in the growing field of LFO analysis. One remaining limitation was the long computational time required for 3-D reconstruction, which prohibited real-time applications. To overcome this limitation, a depth-sensitive diffuse speckle contrast topography (DSCT) method was developed for analyzing scDCT data to achieve fast and high-density 2-D mapping of CBF distribution without the need of complex and time-consuming 3-D reconstructions (Project 2). New head-simulating phantoms with known optical/geometric properties were designed and fabricated to evaluate the spatial resolution and depth sensitivity of DSCT method. In-vivo experiments verified the capability of DSCT in tracking dynamic changes in CBF at different depths during CO2 inhalation and transient cerebral ischemia in rats. In addition to preclinical studies, a low-cost, wearable, fluorescence eye loupe (FLoupe) device was invented for intraoperative visualization of brain tumor margin in the clinic (Project 3). Consistent results were observed against an expensive, large, standard fluorescence operative microscope for the guidance of tumor resection. Overall, through 3 projects this dissertation demonstrated a variety of noninvasive noncontact optical technologies (scDCT, DSCT, and FLoupe) that enabled multiscale (rodents, piglets, and humans) and …


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