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Analytical, Diagnostic and Therapeutic Techniques and Equipment

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Full-Text Articles in Bioimaging and Biomedical Optics

Spectral Characterization Of Colorectal Cancer Using Excitation-Scanning Hyperspectral Imaging, Natalie Hadad May 2026

Spectral Characterization Of Colorectal Cancer Using Excitation-Scanning Hyperspectral Imaging, Natalie Hadad

Honors Theses

Colorectal cancer is one of the most common and deadly cancers worldwide, with a lifetime risk of approximately one in twenty-three for men and one in twenty-five for women. Although early detection significantly improves survival, current diagnostic approaches such as tissue biopsy are invasive, reliant on subjective interpretation, have extended turnaround times, and risk missing flat or depressed lesions that are more difficult to detect than raised polyps. These limitations highlight the need for objective, minimally invasive technologies capable of detecting early tissue changes. This study investigates excitation-scanning hyperspectral imaging (Ex-HSI) as a label-free optical approach for identifying colorectal cancer–associated …


Quantitative Fluorescence Imaging Using A Paired Agent Approach For Improving Surgical Decision Making, Sanjana Pannem Apr 2026

Quantitative Fluorescence Imaging Using A Paired Agent Approach For Improving Surgical Decision Making, Sanjana Pannem

Dartmouth College Ph.D Dissertations

Surgical resection remains to be the cornerstone of treatment for most solid tumors, where the primary objective is to remove all visible and microscopic disease. However, the extent of tumor resection is inherently limited by the surgeon’s ability to distinguish tumor from normal tissue, intraoperatively. As a result, positive surgical margins (PSM), where residual tumor remains after surgery, are a common occurrence and are associated with increased recurrence, need for adjuvant therapies, dismal patient outcomes, and high healthcare costs.

Fluorescence guided surgery (FGS) has emerged as a promising technique to enhance intraoperative visualization of tumors and may help reduce the …


Implementation And Clinical Utility Of Ultra-Low-Field Portable Magnetic Resonance Imaging For Postprocedural Neurological Evaluation In Ambulatory Neurosurgery: Illustrative Cases, Devan Patel, Vinay Jaikumar, Taysia P. T. Morioka, Laz Rifkin, Kenneth S. Jacoby, Jaims Lim, Anais Andrade, Aimee C. Degaetano, Pui Man Rosalind Lai, Elad I. Levy Jan 2026

Implementation And Clinical Utility Of Ultra-Low-Field Portable Magnetic Resonance Imaging For Postprocedural Neurological Evaluation In Ambulatory Neurosurgery: Illustrative Cases, Devan Patel, Vinay Jaikumar, Taysia P. T. Morioka, Laz Rifkin, Kenneth S. Jacoby, Jaims Lim, Anais Andrade, Aimee C. Degaetano, Pui Man Rosalind Lai, Elad I. Levy

EVMS School of Health Professions Faculty Publications

BACKGROUND

Elective endovascular neurosurgical procedures are increasingly performed in ambulatory neurosurgery centers, enabled by advances in catheter technology, safety of conscious sedation, and refined patient selection. Although complication rates are low, rapid evaluation of postprocedural neurological deficits remains critical. Conventional MRI is often impractical in outpatient or procedural settings, whereas ultra-low-field portable MRI (ULF-pMRI) systems (such as Swoop) allow bedside imaging with favorable diagnostic performance.

OBSERVATIONS

Two women in their 60s developed acute neurological deficits at an ambulatory neurosurgery center (ANSC) after diagnostic cerebral angiography in one case and elective internal carotid artery flow diversion in the other. In both …


Advancing Novel Contrast Agents For Applications In Fluorescence-Guided Neurosurgery Using Fluorescence Cryotomography, Augustino Vittorio Scorzo Jun 2025

Advancing Novel Contrast Agents For Applications In Fluorescence-Guided Neurosurgery Using Fluorescence Cryotomography, Augustino Vittorio Scorzo

Dartmouth College Ph.D Dissertations

Fluorescence guided surgery (FGS) is an emerging surgical technique that aims to help surgeons identify tissue types to assist in surgical decision making - ideally providing “cut-by-color” guidance. A primary application for this approach is the identification of tumor tissue to achieve more accurate and complete tumor removal while simultaneously minimizing damage to surrounding normal tissue. The cornerstone of tumor visualization for FGS is the administration of fluorescent contrast agents, or in some cases metabolic precursors, designed to accumulate specifically in tumor tissue, and a wide range of agents that use different targeting mechanisms are currently under investigation. Although these …


Acoustic And Hemodynamic Analysis Of Phantoms: Roughness And Flow Dynamics, Ethan Erik Olof Sundberg Jun 2025

Acoustic And Hemodynamic Analysis Of Phantoms: Roughness And Flow Dynamics, Ethan Erik Olof Sundberg

Master's Theses

The purpose of this study was to determine whether different vascular phantoms, with and without a surrogate arm, could serve as effective analogs to the human brachial artery for assessing endothelial dysfunction, an early indicator of cardiovascular disease, particularly atherosclerosis. Atherosclerosis is characterized by plaque buildup and endothelial damage, which precede more severe clinical events and are often detectable through changes in vascular function. A 40” water tower was used to simulate diastolic pressure, enabling water flow through each phantom. Strain gauge pressure transducers were placed at both ends of the phantoms to measure pressure drop, while a microphone captured …


Development Of A Light-Based Platform To Assess Cervical Mucus Barrier Function And Physical Mucus Properties, Elizabeth J. Buzbee May 2025

Development Of A Light-Based Platform To Assess Cervical Mucus Barrier Function And Physical Mucus Properties, Elizabeth J. Buzbee

McKelvey School of Engineering Graduate Student Theses & Dissertations

Preterm birth is the leading cause of neonatal morbidity and mortality worldwide, yet current clinical tools for predicting its risk lack specificity and reliability. Cervical mucus plays a crucial role in maintaining pregnancy by forming a barrier that protects the uterus against infection. This study investigates the use of laser speckle rheology as a noninvasive technique to assess cervical mucus biomechanics. Synthetic cervical mucus was fabricated at varying hydration levels and tested using a conventional rheometer that confirmed that the mechanical properties of the synthetic mucus samples were representative of physiological cervical mucus. These results were compared to the complex …


Towards The Performance Characterization Of A Robotic Multimodal Diagnostic Imaging System, George Papaioannou, Christos Mitrogiannis, Mark Schweitzer, Nikolaos Michailidis, Maria Pappa, Pegah Khosravi, Apostolos Karantanas, Sean Starling, Christian Ruberg May 2025

Towards The Performance Characterization Of A Robotic Multimodal Diagnostic Imaging System, George Papaioannou, Christos Mitrogiannis, Mark Schweitzer, Nikolaos Michailidis, Maria Pappa, Pegah Khosravi, Apostolos Karantanas, Sean Starling, Christian Ruberg

Publications and Research

Characterizing imaging performance requires a multidisciplinary approach that evaluates various interconnected parameters, including dosage optimization and dynamic accuracy. Radiation dose and dynamic accuracy are challenged by patient motion that results in poor image quality. These challenges are more prevalent in the brain/cardiac pediatric patient imaging, as they relate to excess radiation dose that may be associated with various complications. Scanning vulnerable pediatric patients ought to eliminate anesthesia due to critical risks associated in some cases with intracranial hemorrhages, brain strokes, and congenital heart disease. Some pediatric imaging, however, requires prolonged scanning under anesthesia. It can often be a laborious, suboptimal …


Unified Adaptive Cross-Attention Multimodal Network, Mahesh Sunuwar Mar 2025

Unified Adaptive Cross-Attention Multimodal Network, Mahesh Sunuwar

Shelby Hall Graduate Research Forum Posters

Accurately diagnosing appendicitis remains a significant challenge in emergency medicine due to its varied clinical presentation and overlap with other abdominal conditions. Existing diagnostic models often rely on unimodal data, such as computed tomography (CT) images or clinical notes, limiting their ability to capture the full complexity of patient information. This study proposes a novel multimodal framework, a Unified Adaptive Cross-Attention Multimodal Framework (u-ACM), that integrates CT images and clinical notes using hybrid fusion strategies to improve diagnostic accuracy for appendicitis. The u-ACM leverages adaptive contextual filtering to dynamically remove irrelevant features, crossattention mechanisms to align features between modalities, and …


Explorations Of Dna-Single-Walled Carbon Nanotube Interactions To Develop Multiplexed Molecularly Specific Biosensors For Inflammation, Amelia K. Ryan Jan 2025

Explorations Of Dna-Single-Walled Carbon Nanotube Interactions To Develop Multiplexed Molecularly Specific Biosensors For Inflammation, Amelia K. Ryan

Dissertations and Theses

Inflammatory cytokines such as interleukin-6 (IL-6) and interleukin-12 (IL-12) are central regulators of immune signaling and key biomarkers of disease, yet existing assays for their detection remain slow, invasive, and lack multiplexing ability. This dissertation advances the development of single-walled carbon nanotube (SWCNT) optical nanosensors capable of real-time, multiplexed, and molecularly specific cytokine detection through innovative use of single-stranded DNA (ssDNA) interfaces.

First, an IL-6-specific DNA aptamer was employed as both a dispersing agent and recognition probe for SWCNT fluorescence sensing. Sequence modifications, including anchor domains, truncations, and thermally induced refolding, were systematically tested to optimize sensitivity and selectivity. The …


Cochlear Electrode Insertion Training Model, Sarah Powell, Kaelyn E. Kraley, Nathan J. Smith Jan 2025

Cochlear Electrode Insertion Training Model, Sarah Powell, Kaelyn E. Kraley, Nathan J. Smith

Williams Honors College, Honors Research Projects

Cochlear implant surgery is a delicate procedure performed by Otolaryngologists (ENTs) to implant an electronic device into the inner ear to provide a sense of sound for people who are profoundly deaf or hard of hearing. The current practices of training involve cadavers and 3D-printed models. Cadavers are commonly used but are expensive, single-use, and do not provide visual and haptic feedback, which are essential for medical students. 3D printed models are less commonly used and are hard to fabricate and not as realistic. If medical students are not properly trained for this delicate procedure, then risks are significantly increased …


Adaptive Fusion Neural Networks For Sparse-Angle X-Ray 3d Reconstruction, Shaoyong Hong, Bo Yang, Yan Chen, Hao Quan, Shan Liu, Minyi Tang, Jiawei Tian Jan 2025

Adaptive Fusion Neural Networks For Sparse-Angle X-Ray 3d Reconstruction, Shaoyong Hong, Bo Yang, Yan Chen, Hao Quan, Shan Liu, Minyi Tang, Jiawei Tian

Electrical & Computer Engineering Faculty Publications

3D medical image reconstruction has significantly enhanced diagnostic accuracy, yet the reliance on densely sampled projection data remains a major limitation in clinical practice. Sparse-angle X-ray imaging, though safer and faster, poses challenges for accurate volumetric reconstruction due to limited spatial information. This study proposes a 3D reconstruction neural network based on adaptive weight fusion (AdapFusionNet) to achieve high-quality 3D medical image reconstruction from sparse-angle X-ray images. To address the issue of spatial inconsistency in multi-angle image reconstruction, an innovative adaptive fusion module was designed to score initial reconstruction results during the inference stage and perform weighted fusion, thereby improving …


Nanoparticles For Applications In Specific Diagnostics And Precision Medicine, Naxhije Berisha Feb 2024

Nanoparticles For Applications In Specific Diagnostics And Precision Medicine, Naxhije Berisha

Dissertations, Theses, and Capstone Projects

Heterogeneity is common in the expression of cancer and treatment response. Precision medicine enables healthcare providers to tailor medical care to an individual's distinct genetic and environmental makeup. This customization has the potential to result in more efficient treatments while minimizing side effects. We believe that by studying the interface of nanotechnology and cancer medicine we can elucidate innovative solutions that address the challenges of disease heterogeneity. This includes advancements in drug delivery, formulations development, and diagnostic sensing. We highlight three studies that use nanotechnology for applications in precision medicine. In Chapter 2, we highlight design optimization of drug formulations …


Analyzing Pseudomonas Aeruginosa With Bacteriophage Tags Using Photoacoustic Flow Cytometry, Jennifer C. Schinke Aug 2023

Analyzing Pseudomonas Aeruginosa With Bacteriophage Tags Using Photoacoustic Flow Cytometry, Jennifer C. Schinke

Electronic Theses and Dissertations

The number of daily bacterial infections is climbing and the CDC explains that this is due to the antibiotic-resistant threat in the United States. Finding a faster way of bacterial identification is necessary as it currently takes 1-4 days for a medical lab to culture and identify bacteria. Photoacoustic flow cytometry (PAFC) can be used as an alternative method resulting in swift identification within an hour (Edgar, 2019). Pseudomonas aeruginosa, cell line PA01, will be coated in up to a few hundred red dyed phages making it detectible by the photoacoustic flow cytometry system. Bacteriophages (phages) are viruses that …


Prevention And Reversal Of Elastin-Associated And Phosphate-Dependent Arterial Calcification Using Targeted Nanotherapeutics In Pre-Clinical Models, Fatema Tuj Zohora Aug 2023

Prevention And Reversal Of Elastin-Associated And Phosphate-Dependent Arterial Calcification Using Targeted Nanotherapeutics In Pre-Clinical Models, Fatema Tuj Zohora

All Dissertations

Vascular calcification can be life-threatening, involving calcium phosphate crystal deposits in the blood vessels. The calcification in the intimal layer of the arterial wall is usually associated with atherosclerotic plaque build-up that, in the advanced stage, harbors ‘dispersed’ and ‘spotty’ deposits of calcium phosphate crystals in the necrotic core of the plaque. In contrast, medial arterial calcification (MAC) can form independently of atherosclerosis and appears as ‘Railroad-like’ calcific deposits along degraded elastin lamellae in the medial layer of arteries. The mechanisms of such elastin-associated medial arterial calcification and potential therapies are the key concerns of this dissertation. MAC is common …


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

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 Feb 2023

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 …


Brain Activity Associated With Taste Stimulation: A Mechanism For Neuroplastic Change?, Angela M. Dietsch, Ross M. Westemeyer, Douglas H. Schultz Jan 2023

Brain Activity Associated With Taste Stimulation: A Mechanism For Neuroplastic Change?, Angela M. Dietsch, Ross M. Westemeyer, Douglas H. Schultz

Department of Special Education and Communication Disorders: Faculty Publications

Purpose: Neuroplasticity may be enhanced by increasing brain activation and bloodflow in neural regions relevant to the target behavior.We administered precisely formulated and dosed taste stimuli to determine whether the associated brain activity patterns included areas that underlie swallowing control.

Methods: Five taste stimuli (unflavored, sour, sweet-sour, lemon, and orange suspensions) were administered in timing-regulated and temperature-controlled 3 mL doses via a customized pump/tubing system to 21 healthy adults during functional magnetic resonance imaging (fMRI). Whole-brain analyses of fMRI data assessed main effects of taste stimulation as well as differential effects of taste profile.

Results: Differences in …


Seeing The Big Picture: System Architecture Trends In Endoscopy And Led-Based Hyperspectral Subsystem Intergration, Craig M. Browning Dec 2022

Seeing The Big Picture: System Architecture Trends In Endoscopy And Led-Based Hyperspectral Subsystem Intergration, Craig M. Browning

Graduate Theses and Dissertations (2019 - present)

Early-stage colorectal lesions remain difficult to detect. Early development of neoplasia tends to be small (less than 10 mm) and flat and difficult to distinguish from surrounding mucosa. Additionally, optical diagnosis of neoplasia as benign or malignant is problematic. Low rates of detection of these lesions allow for continued growth in the colorectum and increased risk of cancer formation. Therefore, it is crucial to detect neoplasia and other non-neoplastic lesions to determine risk and guide future treatment. Technology for detection needs to enhance contrast of subtle tissue differences in the colorectum and track multiple biomarkers simultaneously. This work implements one …


Machine Learning And Scalable Informatics Methods To Predict Disease Status From Multimodal Biomedical Data, Hossein Mohammadian Foroushani Aug 2022

Machine Learning And Scalable Informatics Methods To Predict Disease Status From Multimodal Biomedical Data, Hossein Mohammadian Foroushani

McKelvey School of Engineering Graduate Student Theses & Dissertations

Biological understanding of complex diseases such as stroke and obesity is critical for the advancement of medicine. Further knowledge discovery can provide effective biomarkers to improve disease diagnosis and prognosis, identify driver mutations, predict individual genetic susceptibility for early prevention and effective disease management, and facilitate development of personalized drugs. Stroke is the second leading cause of death and long-term disability in the world. Thus, stroke management is a time-sensitive emergency. The initial hours after stroke onset map the trajectory of subsequent neurologic complications. Cerebral edema develops hours to days after acute ischemic stroke and may result in midline shift …


Evaluation And Clinical Implementation Of A Dual-Energy Ct Stopping-Power Ratio Mapping Technique For Proton-Therapy Treatment Planning, Maria Jose Medrano Matamoros Aug 2022

Evaluation And Clinical Implementation Of A Dual-Energy Ct Stopping-Power Ratio Mapping Technique For Proton-Therapy Treatment Planning, Maria Jose Medrano Matamoros

McKelvey School of Engineering Graduate Student Theses & Dissertations

Proton radiotherapy has the potential to treat tumors with better conformal dose distribution than competing modalities when the rapid dose falloff at the end of the proton-beam range is correctly aligned to the edge of the clinical target volume (CTV). However, its clinical potential is dependent on the accurate localization of the Bragg-peak position from predicted stopping-power ratio maps. The method that is most commonly used in today’s clinical practice for predicting stopping-power ratio (SPR) consists of a stoichiometric calibrationtechnique based on single-energy CT (SECT) for direct estimation of patient-specific SPR distribution from vendor-reconstructed Hounsfield Unit (HU) images. Unfortunately, this …


Advancing The Portability, Field Of View, And Spatiotemporal Resolution Of Multi-Parametric Photoacoustic Microscopy, Fenghe Zhong Aug 2022

Advancing The Portability, Field Of View, And Spatiotemporal Resolution Of Multi-Parametric Photoacoustic Microscopy, Fenghe Zhong

McKelvey School of Engineering Graduate Student Theses & Dissertations

Capable of structural, functional, molecular, and metabolic imaging with high spatial resolution in vivo, photoacoustic microscopy (PAM) is an emerging tool in biomedical research. Further, recent advances in multi-parametric acquisition and analysis make PAM uniquely capable of simultaneously mapping the total concentration of hemoglobin (CHb), oxygen saturation of hemoglobin (sO2), and blood flow speed. However, there are multiple major limitations, including, the large footprint, low imaging speed, limited imaging contrast, and insufficient axial resolution, which impedance its applications in basic and translational research. In this dissertation, I presented potential solutions to overcome the limitations above.In the first part of this …


Cbct In Clinical Practice, Tarunjeet Pabla Bds, Dmd, Ms, Dip. Abomr, Hugo C. Campos Dds, Dmd, Mds, Dip. Abomr, Aruna Ramesh Bds, Dmd, Ms, Dip. Abomr Mar 2022

Cbct In Clinical Practice, Tarunjeet Pabla Bds, Dmd, Ms, Dip. Abomr, Hugo C. Campos Dds, Dmd, Mds, Dip. Abomr, Aruna Ramesh Bds, Dmd, Ms, Dip. Abomr

The Journal of the Michigan Dental Association

This feature explores the integration of Cone Beam Computed Tomography (CBCT) into dental practice, offering guidelines for best practices. Introduced in 2001, CBCT revolutionized dental radiography, impacting various clinical areas. The article emphasizes the need for clinicians to comprehend CBCT technology, its benefits, and potential risks. It delves into CBCT imaging considerations, technical parameters (Field of View, Voxel Size, Spatial and Contrast Resolution), image viewing, artifacts, machine calibration, and service. Addressing radiation dose, risks, and protection, the article outlines decision-making for 2D vs. 3D imaging. It underscores the responsibility of interpreting CBCT images, legal considerations, return on investment, and the …


Toward A Multimodal Computer-Aided Diagnostic Tool For Alzheimer’S Disease Conversion, Danilo Pena, Jessika Suescun, Mya Schiess, Timothy M. Ellmore, Luca Giancardo, Alzheimer’S Disease Neuroimaging Initiative Jan 2022

Toward A Multimodal Computer-Aided Diagnostic Tool For Alzheimer’S Disease Conversion, Danilo Pena, Jessika Suescun, Mya Schiess, Timothy M. Ellmore, Luca Giancardo, Alzheimer’S Disease Neuroimaging Initiative

Publications and Research

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder. It is one of the leading sources of morbidity and mortality in the aging population AD cardinal symptoms include memory and executive function impairment that profoundly alters a patient’s ability to perform activities of daily living. People with mild cognitive impairment (MCI) exhibit many of the early clinical symptoms of patients with AD and have a high chance of converting to AD in their lifetime. Diagnostic criteria rely on clinical assessment and brain magnetic resonance imaging (MRI). Many groups are working to help automate this process to improve the clinical workflow. Current …


Deep Learning Approach To Improved Image Quality For Medical Diagnostics, Olivia Loesch, Katie Leyba, Halyley Chan, Craig Goergen Dec 2021

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 …


Development Of Quantitative Molecular Photoacoustic Imaging For Noninvasive Cancer Diagnostics, Cayla Zandbergen Aug 2021

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

Dissertations and 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 …


Focused Ultrasound-Mediated Drug Delivery To The Brainstem, Dezhuang Ye Jan 2021

Focused Ultrasound-Mediated Drug Delivery To The Brainstem, Dezhuang Ye

McKelvey School of Engineering Graduate Student Theses & Dissertations

Brainstem gliomas are tumors that occur in the brainstem, the brain region that connects the brain to the spinal cord and controls vital body functions. The critical anatomic location of the brainstem precludes surgical intervention and limits the use of invasive therapeutic techniques. Moreover, the frequently intact blood-brain barrier (BBB) of most brainstem gliomas prevents therapeutic agents from reaching the diseased site. The currently available techniques for brain drug delivery are either invasive (e.g., convection-enhanced delivery) or lack targeting to the diseased site (e.g., intranasal brain drug delivery). Novel techniques that can noninvasively overcome the BBB are critically needed for …


Multi-Dimensional Extension Of The Alternating Minimization Algorithm In X-Ray Computed Tomography, Jingwei Lu Aug 2019

Multi-Dimensional Extension Of The Alternating Minimization Algorithm In X-Ray Computed Tomography, Jingwei Lu

McKelvey School of Engineering Graduate Student Theses & Dissertations

X-ray computed tomography (CT) is an important and effective tool in medical and industrial

imaging applications. The state-of-the-art methods to reconstruct CT images have had

great development but also face challenges. This dissertation derives novel algorithms to

reduce bias and metal artifacts in a wide variety of imaging modalities and increase performance

in low-dose scenarios.

The most widely available CT systems still use the single-energy CT (SECT), which is

good at showing the anatomic structure of the patient body. However, in SECT image

reconstruction, energy-related information is lost. In applications like radiation treatment

planning and dose prediction, accurate energy-related information …


Multi-Dimensional Extension Of The Alternating Minimization Algorithm In X-Ray Computed Tomography, Jingwei Lu Aug 2019

Multi-Dimensional Extension Of The Alternating Minimization Algorithm In X-Ray Computed Tomography, Jingwei Lu

McKelvey School of Engineering Graduate Student Theses & Dissertations

X-ray computed tomography (CT) is an important and effective tool in medical and industrial imaging applications. The state-of-the-art methods to reconstruct CT images have had great development but also face challenges. This dissertation derives novel algorithms to reduce bias and metal artifacts in a wide variety of imaging modalities and increase performance in low-dose scenarios. The most widely available CT systems still use the single-energy CT (SECT), which is good at showing the anatomic structure of the patient body. However, in SECT image reconstruction, energy-related information is lost. In applications like radiation treatment planning and dose prediction, accurate energy-related information …


Seeing Eye To Eye: A Machine Learning Approach To Automated Saccade Analysis, Maigh Attre May 2019

Seeing Eye To Eye: A Machine Learning Approach To Automated Saccade Analysis, Maigh Attre

Honors Scholar Theses

Abnormal ocular motility is a common manifestation of many underlying pathologies particularly those that are neurological. Dynamics of saccades, when the eye rapidly changes its point of fixation, have been characterized for many neurological disorders including concussions, traumatic brain injuries (TBI), and Parkinson’s disease. However, widespread saccade analysis for diagnostic and research purposes requires the recognition of certain eye movement parameters. Key information such as velocity and duration must be determined from data based on a wide set of patients’ characteristics that may range in eye shapes and iris, hair and skin pigmentation [36]. Previous work on saccade analysis has …


Quantifying Iron Overload Using Mri, Active Contours, And Convolutional Neural Networks, Andrea Sajewski, Stacey Levine Apr 2019

Quantifying Iron Overload Using Mri, Active Contours, And Convolutional Neural Networks, Andrea Sajewski, Stacey Levine

Undergraduate Research and Scholarship Symposium

Iron overload, a complication of repeated blood transfusions, can cause tissue damage and organ failure. The body has no regulatory mechanism to excrete excess iron, so iron overload must be closely monitored to guide therapy and measure treatment response. The concentration of iron in the liver is a reliable marker for total body iron content and is now measured noninvasively with magnetic resonance imaging (MRI). MRI produces a diagnostic image by measuring the signals emitted from the body in the presence of a constant magnetic field and radiofrequency pulses. At each pixel, the signal decay constant, T2*, can be calculated, …