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Frequency Dependent Diffusion Kurtosis Measurement In The Human Brain With Oscillating Gradients, Kevin B. Borsos 2021 The University of Western Ontario

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 2021 University of Wisconsin-Milwaukee

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 2021 The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences

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 2021 CUNY City College

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 2021 Memorial Sloan-Kettering Cancer Center

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 2021 Western University

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 2021 University of Arkansas, Fayetteville

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 2021 The University of Western Ontario

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 PhaseWareTM that allows novice to experienced users to …


K-Wire Differentiation, Oluwadamilola Oluwadara, Lillian Maresco, Eunjung Lee, Michelle De Leon 2021 Union College - Schenectady, NY

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 2021 New Jersey Institute of Technology

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 2021 Washington University in St. Louis

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 2021 Duquesne University

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 2021 Duquesne University

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 2021 University of Kentucky

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 (kw). 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 2021 Electrical Engineering and Computer Science Department

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 2021 University of Tennessee, Knoxville

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 2021 University of Arkansas, Fayetteville

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 2021 University of Arkansas, Fayetteville

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 …


Statistical Machine Learning For Breast Cancer Detection With Terahertz Imaging, Tanny Andrea Chavez Esparza 2021 University of Arkansas, Fayetteville

Statistical Machine Learning For Breast Cancer Detection With Terahertz Imaging, Tanny Andrea Chavez Esparza

Graduate Theses and Dissertations

Breast conserving surgery (BCS) is a common breast cancer treatment option, in which the cancerous tissue is excised while leaving most of the healthy breast tissue intact. The lack of in-situ margin evaluation unfortunately results in a re-excision rate of 20-30% for this type of procedure. This study aims to design statistical and machine learning segmentation algorithms for the detection of breast cancer in BCS by using terahertz (THz) imaging. Given the material characterization properties of the non-ionizing radiation in the THz range, we intend to employ the responses from the THz system to identify healthy and cancerous breast tissue …


Development Of Quantitative Ultrasound-Mediated Molecular Imaging Of The Tumor Microenvironment, Trevor Mitcham 2021 The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences

Development Of Quantitative Ultrasound-Mediated Molecular Imaging Of The Tumor Microenvironment, Trevor Mitcham

Dissertations & Theses (Open Access)

While conventional diagnostic imaging modalities provide anatomical information to clinicians, these techniques are not sensitive to critical physiological processes. In order to properly classify cancer, it is necessary to investigate noninvasive methods which can provide insight into these processes, allowing clinicians to determine personalized therapeutic options. Therefore, molecular imaging is focused on visualization and characterization of biomarkers within the tumor microenvironment (TME), which can then be combined with the anatomical information provided from diagnostic imaging.

Two such biomarkers of interest are blood oxygen saturation (SO2) and cell receptor expression. SO2 is a measure of the fraction of …


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