Bioimaging and Biomedical Optics Commons^™

Deep Learning Approach To Improved Image Quality For Medical Diagnostics, Olivia Loesch, Katie Leyba, Halyley Chan, Craig Goergen

Discovery Undergraduate Interdisciplinary Research Internship

The United Nation’s health-related Sustainable Development Goals are difficult to achieve in low- and middle-income countries due to workforce shortages and inadequate health surveillance systems. However, with the growth of artificial intelligence (AI) and computer algorithms, it is possible to apply AI to healthcare technologies to improve progress towards these UN standards. This project aims at using and improving computer algorithms and deep learning to aid in the extraction of important structural and functional information from murine carotid artery ultrasound and photoacoustic images. First, we created a large database of simulated photoacoustic images to optimize the algorithms. These images were …

Inter-Subject Correlation While Listening To Minimalist Music: A Study Of Electrophysiological And Behavioral Responses To Steve Reich’S Piano Phase, Tysen Dauer, Duc T. Nguyen, Nick Gang, Jacek P. Dmochowski, Jonathan Berger, Blair Kaneshiro

Publications and Research

Musical minimalism utilizes the temporal manipulation of restricted collections of rhythmic, melodic, and/or harmonic materials. One example, Steve Reich’s Piano Phase, offers listeners readily audible formal structure with unpredictable events at the local level. For example, pattern recurrences may generate strong expectations which are violated by small temporal and pitch deviations. A hyper-detailed listening strategy prompted by these minute deviations stands in contrast to the type of listening engagement typically cultivated around functional tonal Western music. Recent research has suggested that the inter-subject correlation (ISC) of electroencephalographic (EEG) responses to natural audio-visual stimuli objectively indexes a state of “engagement,” demonstrating …

Design Of Miniaturized Antipodal Vivaldi Antennas And A Microwave Head Imaging System For The Detection Of Blood Clots In The Brain, Farhana Parveen

Electronic Theses and Dissertations, 2020-

Traditional brain imaging modalities, for example, MRI, CT scan, X-ray, etc. can provide precise and high-resolution images of the brain for diagnosing lesions, tumors or clots inside the brain. However, these modalities require bulky and expensive test setups accessible only at specialized diagnostic centers, and hence may not be suitable or affordable to many patients. Furthermore, the inherent health risks limit the usability of these modalities for frequent monitoring. Microwave imaging is deemed a promising alternative due to its being cost-effective, portable, non-ionizing, non-intrusive. Therefore, this work aims to design an effective microwave head imaging system for the detection of …

Generation, Analysis, And Evaluation Of Patient-Specific, Osteoligamentous, Spine Meshes, Austin R. Tapp

Biomedical Engineering Theses & Dissertations

Scoliosis, an abnormal curvature of the spine, is traditionally corrected with bracing treatments or by a highly invasive posterior spinal fusion (PSF) operation. These correction strategies are constrained by current imaging modalities, which fail to elucidate the soft tissue anatomy that is known to play a critical role in spinal stiffness and overall structure. Osteoligamentous segmentations of the spinal column offer a foundation for downstream finite element (FE) studies seeking to optimize bracing treatments or determine ideal surgical approaches.

This thesis presents methods for automatically and semi-automatically segmenting vertebrae and surrounding soft tissues of the spinal column using X-ray computed …

Time-Lapse Observation Of Sarcomeric Addition In Hypertrophic Models Based On A Tissue Like Cardiomyocyte Culture, Ailin Wei

All Dissertations

Cardiac hypertrophy is the response of the heart to increased mechanical stress exerted on the heart. In a hypertrophic heart, the muscles elongate or/and thicken with cardiomyocytes growing sizes. It is assumed that cardiomyocytes elongate by adding sarcomeres in series; the cardiomyocytes thicken with the addition of sarcomeres in the parallel position.

In this study, a tissue-like culture model was achieved with step-like ICDs. Uniaxial static stretch has been applied to our unique culture model for studying mechanical-load-induced cardiac hypertrophy. Hypertrophic responses of these cardiomyocytes have been confirmed on transcriptional and translational levels in our tissue-like model. The two-photon excitation …

Single-Molecule Localization Microscopy Of 3d Orientation And Anisotropic Wobble Using A Polarized Vortex Point Spread Function, Tianben Ding, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

Within condensed matter, single fluorophores are sensitive probes of their chemical environments, but it is difficult to use their limited photon budget to image precisely their positions, 3D orientations, and rotational diffusion simultaneously. We demonstrate the polarized vortex point spread function (PSF) for measuring these parameters, including characterizing the anisotropy of a molecule’s wobble, simultaneously from a single image. Even when imaging dim emitters (∼500 photons detected), the polarized vortex PSF can obtain 12 nm localization precision, 4°–8° orientation precision, and 26° wobble precision. We use the vortex PSF to measure the emission anisotropy of fluorescent beads, the wobble dynamics …

Correlation Of Acute Radiation Dermatitis To Tissue Oxygenation In Radiation Therapy Treated Breast Cancer Subjects, Edwin Alexander Robledo

FIU Electronic Theses and Dissertations

Over 95% of radiation therapy (RT) treated breast cancer subjects undergo an adverse skin reaction known as radiation dermatitis (RD). Assessment of severity or grading of RD is clinically visual and hence subjective. Our objective is to determine sub-clinical tissue oxygenation (StO₂) changes in response to RT treatment in breast cancer subjects using near-infrared spectroscopic imaging and correlate these changes to RD grading. A WIRB approved 6-8 week longitudinal pilot study was carried out on 10 RT-treated subjects at Miami Cancer Institute. Significant changes (p < 0.05) in StO₂ of irradiated and contralateral chest wall and axilla regions with weeks of …

Dataset Of Concurrent Eeg, Ecg, And Behavior With Multiple Doses Of Transcranial Electrical Stimulation, Nigel Gebodh, Zeinab Esmaeilpour, Abhishek Datta, Marom Bikson

Publications and Research

We present a dataset combining human-participant high-density electroencephalography (EEG) with physiological and continuous behavioral metrics during transcranial electrical stimulation (tES). Data include within participant application of nine High-Definition tES (HD-tES) types, targeting three cortical regions (frontal, motor, parietal) with three stimulation waveforms (DC, 5 Hz, 30 Hz); more than 783 total stimulation trials over 62 sessions with EEG, physiological (ECG, EOG), and continuous behavioral vigilance/alertness metrics. Experiment 1 and 2 consisted of participants performing a continuous vigilance/alertness task over three 70-minute and two 70.5-minute sessions, respectively. Demographic data were collected, as well as self-reported wellness questionnaires before and after each …

Pairwise Correlation Analysis Of The Alzheimer’S Disease Neuroimaging Initiative (Adni) Dataset Reveals Significant Feature Correlation, Erik D. Huckvale, Matthew W. Hodgman, Brianna B. Greenwood, Devorah O. Stucki, Katrisa M. Ward, Mark T. W. Ebbert, John S. K. Kauwe, The Alzheimer’S Disease Neuroimaging Initiative, The Alzheimer’S Disease Metabolomics Consortium, Justin B. Miller

Sanders-Brown Center on Aging Faculty Publications

The Alzheimer’s Disease Neuroimaging Initiative (ADNI) contains extensive patient measurements (e.g., magnetic resonance imaging [MRI], biometrics, RNA expression, etc.) from Alzheimer’s disease (AD) cases and controls that have recently been used by machine learning algorithms to evaluate AD onset and progression. While using a variety of biomarkers is essential to AD research, highly correlated input features can significantly decrease machine learning model generalizability and performance. Additionally, redundant features unnecessarily increase computational time and resources necessary to train predictive models. Therefore, we used 49,288 biomarkers and 793,600 extracted MRI features to assess feature correlation within the ADNI dataset to determine the …

Artificial Image Objects For Classification Of Breast Cancer Biomarkers With Transcriptome Sequencing Data And Convolutional Neural Network Algorithms, Xiangning Chen, Daniel G. Chen, Zhongming Zhao, Justin M. Balko, Jingchun Chen

School of Medicine Faculty Publications

Background: Transcriptome sequencing has been broadly available in clinical studies. However, it remains a challenge to utilize these data effectively for clinical applications due to the high dimension of the data and the highly correlated expression between individual genes. Methods: We proposed a method to transform RNA sequencing data into artificial image objects (AIOs) and applied convolutional neural network (CNN) algorithms to classify these AIOs. With the AIO technique, we considered each gene as a pixel in an image and its expression level as pixel intensity. Using the GSE96058 (n = 2976), GSE81538 (n = 405), and GSE163882 (n = …

Using Computer Vision To Track Anatomical Structures During Cochlear Implant Surgery, Nicholas Bach

McKelvey School of Engineering Theses & Dissertations

There is a steep learning curve for surgeons performing cochlear implant surgeries. We aimed to use computer vision to track anatomical features with the goal of helping surgeons perform cochlear implant surgery without damaging the cochlea. We compared nine algorithms in total, seven object tracking algorithms and two optical flow algorithms utilizing the LucasKanade method, on manually created cochlear implant surgery videos to determine the accuracy associated with each. Compared with eight other algorithms, we observed that an iterative pyramidal implementation of the Lucas-Kanade (IPLK) method, implemented through OpenCV, performed the best. The IPLK method had the lowest error rate …

Frequency Dependent Diffusion Kurtosis Measurement In The Human Brain With Oscillating Gradients, Kevin B. Borsos

Electronic Thesis and Dissertation Repository

Oscillating gradient spin-echo (OGSE) is an implementation of diffusion MRI that enables shorter effective diffusion times than the conventional pulse gradient spin-echo (PGSE) by periodically modulating the diffusion gradient. Measurements of the diffusion kurtosis, which reflects the degree of restricted diffusion, have previously been prohibited with OGSE due to technical limitations of clinical gradient systems. This thesis presents a novel oscillating gradient waveform that enables the measurement of kurtosis using OGSE without requiring advanced gradient hardware. Decreases of kurtosis are observed in OGSE acquisitions of healthy human subjects relative to PGSE, demonstrating the dependence of the kurtosis on oscillation frequency. …

Medical Image Segmentation Using Machine Learning, Masoud Khani

Theses and Dissertations

Image segmentation is the most crucial step in image processing and analysis. It can divide an image into meaningfully descriptive components or pathological structures. The result of the image division helps analyze images and classify objects. Therefore, getting the most accurate segmented image is essential, especially in medical images. Segmentation methods can be divided into three categories: manual, semiautomatic, and automatic. Manual is the most general and straightforward approach. Manual segmentation is not only time-consuming but also is imprecise. However, automatic image segmentation techniques, such as thresholding and edge detection, are not accurate in the presence of artifacts like noise …

Development Of Quantitative Molecular Photoacoustic Imaging For Noninvasive Cancer Diagnostics, Cayla Zandbergen

Dissertations & Theses (Open Access)

Traditional diagnostic imaging provides clinicians with anatomical information that guides both diagnosis and treatment planning; however, once a tumor has progressed enough to be visible, it has often reached an advanced stage. Molecular imaging techniques allow for real-time visualization of chemical and biological processes via imaging of specific biomarkers, which can facilitate detection of malignancies before they become visible. One biomarker of interest is blood oxygen saturation (SO₂) due to its correlation with hypoxia, which is associated with increased tumor malignancy; some studies have also established SO₂ as an independent biomarker of disease progression. Additionally, because cancerous …

Association Of X-Ray Absorptiometry Body Composition Measurements With Basic Anthropometrics And Mortality Hazard, Nir Y. Krakauer, Jesse C. Krakauer

Publications and Research

Dual-energy X-ray absorptiometry (DEXA) is a non-invasive imaging modality that can estimate whole-body and regional composition in terms of fat, lean, and bone mass. We examined the ability of DEXA body composition measures (whole-body, trunk, and limb fat mass and fat-free mass) to predict mortality in conjunction with basic body measures (anthropometrics), expressed using body mass index (BMI) and a body shape index (ABSI). We used data from the 1999–2006 United States National Health and Nutrition Examination Survey (NHANES), with mortality follow-up to 2015. We found that all DEXA-measured masses were highly correlated with each other and with ABSI and …

Pathcnn: Interpretable Convolutional Neural Networks For Survival Prediction And Pathway Analysis Applied To Glioblastoma, Jung Hun Oh, Wookjin Choi, Euiseong Ko, Mingon Kang, Allen Tannenbaum, Joseph O. Deasy

Computer Science Faculty Research

Motivation: Convolutional neural networks (CNNs) have achieved great success in the areas of image processing and computer vision, handling grid-structured inputs and efficiently capturing local dependencies through multiple levels of abstraction. However, a lack of interpretability remains a key barrier to the adoption of deep neural networks, particularly in predictive modeling of disease outcomes. Moreover, because biological array data are generally represented in a non-grid structured format, CNNs cannot be applied directly. Results: To address these issues, we propose a novel method, called PathCNN, that constructs an interpretable CNN model on integrated multi-omics data using a newly defined pathway image. …

Rapid Microscopic Fractional Anisotropy Imaging Via An Optimized Linear Regression Formulation., N J J Arezza, D H Y Tse, C A Baron

Medical Biophysics Publications

Water diffusion anisotropy in the human brain is affected by disease, trauma, and development. Microscopic fractional anisotropy (μFA) is a diffusion MRI (dMRI) metric that can quantify water diffusion anisotropy independent of neuron fiber orientation dispersion. However, there are several different techniques to estimate μFA and few have demonstrated full brain imaging capabilities within clinically viable scan times and resolutions. Here, we present an optimized spherical tensor encoding (STE) technique to acquire μFA directly from the 2nd order cumulant expansion of the powder averaged dMRI signal obtained from direct linear regression (i.e. diffusion kurtosis) which requires fewer powder-averaged signals than …

Experimental And Analysis Of Electromagnetic Characterization Of Biological And Non-Biological Materials In Microwave, Millimeter-Wave, And Terahertz Frequency Bands, Nagma Vohra

Graduate Theses and Dissertations

The goal of this research is to characterize the electromagnetic properties of biological and non-biological materials at terahertz (THz), millimeter-wave, and microwave frequency bands. The biological specimens are measured using the THz imaging and spectroscopy system, whereas the non-biological materials are measured using the microwave and millimeter-wave free-space system. These facilities are located in the Engineering Research Center at the University of Arkansas. The THz imaging system (TPS 3000) uses a Ti-Sapphire laser directed on the photoconductive antennas to generate a THz time domain pulse. Upon using the Fourier Transform, the spectrum of the pulsed THz signal includes frequencies from …

Snapshot Three-Dimensional Surface Imaging With Multispectral Fringe Projection Profilometry, Parsa Omidi

Electronic Thesis and Dissertation Repository

Fringe Projection Profilometry (FPP) is a popular method for non-contact optical surface measurements, including motion tracking. The technique derives 3D surface maps from phase maps estimated from the distortions of fringe patterns projected onto the surface of an object. Estimation of phase maps is commonly performed with spatial phase retrieval algorithms that use a series of complex data processing stages. Researchers must have advanced data analysis skills to process FPP data due to a lack of availability of simple research-oriented software tools. Chapter 2 describes a comprehensive FPP software tool called PhaseWare^TM that allows novice to experienced users to …

K-Wire Differentiation, Oluwadamilola Oluwadara, Lillian Maresco, Eunjung Lee, Michelle De Leon

Honors Theses

Kirschner Pins, known as K-wires, are smooth sharp stainless steel pins used in the field of orthopedics to stabilize bone fracture fragments in their correct position until they have fully healed. K-wires are most commonly used for comminuted metaphyseal fractures of the long bones, and fractures of smaller bones such as the phalanges. The wires are inserted into bone via a drill and the ends of the wire are bent and left outside of the body for easy removal once the bone has healed. The surgeon uses x-ray images to guide K-wire insertion, ensure proper internal alignment, and determine if …

Development Of Deep Learning Neural Network For Ecological And Medical Images, Shaobo Liu

Dissertations

Deep learning in computer vision and image processing has attracted attentions from various fields including ecology and medical image. Ecologists are interested in finding an effective model structure to classify different species. Tradition deep learning model use a convolutional neural network, such as LeNet, AlexNet, VGG models, residual neural network, and inception models, are first used on classifying bee wing and butterfly datasets. However, insufficient data sample and unbalanced samples in each class have caused a poor accuracy. To make improvement the test accuracy, data augmentation and transfer learning are applied. Recently developed deep learning framework based on mathematical morphology …

Injectable Ct/Mri Contrast Agent For Gastrointestinal Tumor Tracking, Luna Zhang

McKelvey School of Engineering Theses & Dissertations

Gastrointestinal cancers remain to be of the most common and deadly cancers worldwide. Early detection and treatments are crucial for reducing mortality and improving patient outcome. Radiation therapy is a non-invasive localized tumor treatment method, and utilizes radiation to kill the cancerous cells and shrink tumors at specific sites. Precise localization at the target tumor site is therefore important before radiation therapy, especially for gastrointestinal tumor sites located in the moving bowel. Currently, invasive endoscopies along with ink tattoos are used for identifying tumor location, which often require sedation and bring much discomfort. Imaging tests, including CT and MRI, play …

Diagnosis Of Melanoma Disease State From Patient Blood Samples Using Photoacoustic Flow Cytometry, Jacob Salvatore

Electronic Theses and Dissertations

Approximately 1 in 50 Americans develop melanoma in their lifetime. Early detection of melanoma is pivotal to the survival of the patient, with a 99% survival rate for 5 or more years after an early diagnosis. Metastasis, or the spread of cancer, increases the chances of cancerous growth in other parts of the body. In this study, we propose the use of photoacoustic flow cytometry as a diagnostic of patient disease state, by closely monitoring the amount of circulating melanoma cells (CMCs) in a patient’s blood before and after chemotherapy treatments. Using this patient data, we were able to make …

Detecting A Heterogenous Sample Of Pigmented Melanoma Cell Lines Using Photoacoustic Flow Cytometry, Margaret Cappellano

Electronic Theses and Dissertations

Metastatic melanoma is the deadliest form of skin cancer, which is in part, attributed to its rapid aggression and lack of response to typical treatment methods. There are far too often cases where a lymph node biopsy does not detect the severity of the cancer, which in turn causes a lack of diagnosis until a mass can be visually detected on a scan, such as a PET, CT, or MRI. Once visible on a scan, the cancer is too progressive for successful treatment. To avoid this, we investigated how a blood sample can be used to negate a missed diagnosis, …

Water Exchange Rate Across The Blood-Brain Barrier Is Associated With Csf Amyloid-Β 42 In Healthy Older Adults, Brian T. Gold, Xingfeng Shao, Tiffany L. Sudduth, Gregory A. Jicha, Donna M. Wilcock, Elayna R. Seago, Danny J. J. Wang

Sanders-Brown Center on Aging Faculty Publications

INTRODUCTION: We tested if water exchange across the blood-brain barrier (BBB), estimated with a noninvasive magnetic resonance imaging (MRI) technique, is associated with cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease (AD) and neuropsychological function.

METHODS: Forty cognitively normal older adults (67–86 years old) were scanned with diffusion‐prepared, arterial spin labeling (DP‐ASL), which estimates water exchange rate across the BBB (k_w). Participants also underwent CSF draw and neuropsychological testing. Multiple linear regression models were run with kw as a predictor of CSF concentrations and neuropsychological scores.

RESULTS: In multiple brain regions, BBB kw was positively associated with CSF amyloid …

Non-Contact Techniques For Human Vital Sign Detection And Gait Analysis, Farnaz Foroughian

Doctoral Dissertations

Human vital signs including respiratory rate, heart rate, oxygen saturation, blood pressure, and body temperature are important physiological parameters that are used to track and monitor human health condition. Another important biological parameter of human health is human gait. Human vital sign detection and gait investigations have been attracted many scientists and practitioners in various fields such as sport medicine, geriatric medicine, bio-mechanic and bio-medical engineering and has many biological and medical applications such as diagnosis of health issues and abnormalities, elderly care and health monitoring, athlete performance analysis, and treatment of joint problems. Thoroughly tracking and understanding the normal …

Optically Active Rare-Earth Doped Films Synthesized By Pulsed Laser Deposition For Biomedical Applications, Charles William Bond

Doctoral Dissertations

Optically active materials are used in many biomedical applications ranging from medical imaging to light therapies. Investigating the effects of differing nanostructure configurations on the optical performance of these materials can improve tunability, efficiency, and practicality for their respective applications. This work utilizes pulsed laser deposition (PLD) to develop nanostructured thin films and determines their optical performance for applications in computed radiography for medical imaging and in LEDs which can be used in biomedical applications such as photobiomodulation.

In computed radiography, scattering of the stimulation light by the storage phosphor crystal grain boundaries in imaging plates negatively impacts spatial resolution. …

Quantifying Blood Flow Patterns In The Pediatric Heart Using Blood Speckle Imaging, Harrison Dean

Biomedical Engineering Undergraduate Honors Theses

Congenital Heart Disease (CHD) is the most common type of congenital disease worldwide. Echocardiography using Doppler ultrasound is typically used to diagnose and monitor CHD; however, it is angle-dependent in nature and as a result is limited in its ability to accurately evaluate ventricular function. Blood Speckle Imaging (BSI) is a novel, angle-independent imaging modality that provides detailed blood flow information and visualization within a given area using speckle-tracking. In this study, velocity-field information obtained from BSI was used to calculate flow parameters such as kinetic energy (KE) and circulation using a custom created MATLAB program. BSI was performed on …

Metabolic Profiling Of Radiation Resistance In Head And Neck Squamous Cell Carcinoma, Natalie Curry

Biomedical Engineering Undergraduate Honors Theses

Abstract

Head and neck squamous cell carcinoma is the sixth most common cancer worldwide. Radiation therapy is one of the most common treatments for HNSCC, however, many patients do not respond to radiation therapy. Currently, it takes about a month for clinicians to definitively determine whether a tumor is responsive to radiation therapy. Current studies have identified that the prevention of mitochondrial oxidative stress caused by reactive oxygen species can prevent DNA damage and lead to a decrease in apoptosis in radiation resistant cells Measuring the oxygen consumption rate through Seahorse metabolic assays allows us to quantify basal respiration, maximal …

Monitoring Fgf1-Treated Skin Wounds With Label-Free Multiphoton Microscopy, Gianna Busch

Biomedical Engineering Undergraduate Honors Theses

Chronic skin wounds pose a significant threat to public health, affecting as many as 5.5 million people in the United States every year and costing the healthcare system $10 billion annually^1,2. These wounds are associated with prolonged inflammation, poor vascularization, increased infection risk, and high mortality rates^3,4. There is significant interest in developing and testing a variety of biologics to promote wound healing. However, quantitative evaluations of healing are typically limited to measurements of wound size, and there is a critical need to develop quantitative biomarkers sensitive to different aspects of the healing process. Label-free multiphoton …