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Full-Text Articles in Biomedical Engineering and Bioengineering

Iron Nanoparticles For Magnetic Imaging Applications, Aleia Williams Dec 2022

Iron Nanoparticles For Magnetic Imaging Applications, Aleia Williams

Masters Theses

Extensive research on iron oxide nanoparticles for various applications including nanomedicine, energy applications, environmental remediation, and magnetic imaging have previously been performed. Many are currently FDA approved as magnetic resonance imaging contrast agents and tracers for magnetic particle imaging applications. Magnetic properties of such materials are crucial to obtain good contrast and resolution. However, studies have shown the magnetic properties of iron oxide nanoparticles are less in comparison to those found in pure iron nanoparticle.

This research involves the synthesis and characterization of iron nanoparticles for applications in magnetic resonance imaging contrast agents, magnetic particle imaging tracers, and therapeutic agents …


Imaging Potential In Saturation Recovery Methods For Sarcoidosis Patients With Medical Devices, Samantha Zhao Jan 2021

Imaging Potential In Saturation Recovery Methods For Sarcoidosis Patients With Medical Devices, Samantha Zhao

Theses and Dissertations

Cardiovascular magnetic resonance (CMR) imaging is a preferred imaging methodology due to its lack of ionizing radiation and ability to detect myocardial inflammation and fibrosis using quantitative T1 mapping techniques. Cardiac sarcoidosis (CS) is characterized as the formation of granulomas in the myocardium. Current methods for detection include measuring non-cardiac specific C-reactive protein (CRP) levels, or PET imaging, which uses ionizing radiation, therefore CMR would make an ideal imaging option. However, many CS patients have implanted cardiac devices which can cause degradation in image. The modified Look-Locker inversion recovery (MOLLI) method is widely used in quantitative T1 mapping with high …


Perceptually Improved Medical Image Translations Using Conditional Generative Adversarial Networks, Anurag Vaidya Jan 2021

Perceptually Improved Medical Image Translations Using Conditional Generative Adversarial Networks, Anurag Vaidya

Honors Theses

Magnetic resonance imaging (MRI) can help visualize various brain regions. Typical MRI sequences consist of T1-weighted sequence (favorable for observing large brain structures), T2-weighted sequence (useful for pathology), and T2-FLAIR scan (useful for pathology with suppression of signal from water). While these different scans provide complementary information, acquiring them leads to acquisition times of ~1 hour and an average cost of $2,600, presenting significant barriers. To reduce these costs associated with brain MRIs, we present pTransGAN, a generative adversarial network capable of translating both healthy and unhealthy T1 scans into T2 scans. We show that the addition of non-adversarial …


A 3d Printed Axon-Mimetic Diffusion Mri Phantom, Tristan K. Kuehn Aug 2020

A 3d Printed Axon-Mimetic Diffusion Mri Phantom, Tristan K. Kuehn

Electronic Thesis and Dissertation Repository

Diffusion MRI is used to non-invasively characterize the microstructure of the brain. However, the accuracy of the characterization is difficult to verify because no other non-invasive imaging modality provides the same information. This thesis presents a novel 3D printed axon-mimetic (3AM) diffusion MRI phantom, a synthetic object designed to mimic the brain's microstructure.

The phantoms were characterized using microscopy, synchrotron micro-computed tomography, and diffusion MRI, and found to have sufficiently axon-mimetic properties to be useful as diffusion MRI phantoms. A set of phantoms designed to have anatomically realistic and complex fibre structures was used to test the response of diffusion …


Incorporating Cardiac Substructures Into Radiation Therapy For Improved Cardiac Sparing, Eric Daniel Morris Jan 2020

Incorporating Cardiac Substructures Into Radiation Therapy For Improved Cardiac Sparing, Eric Daniel Morris

Wayne State University Dissertations

Growing evidence suggests that radiation therapy (RT) doses to the heart and cardiac substructures (CS) are strongly linked to cardiac toxicities, though only the heart is considered clinically. This work aimed to utilize the superior soft-tissue contrast of magnetic resonance (MR) to segment CS, quantify uncertainties in their position, assess their effect on treatment planning and an MR-guided environment.

Automatic substructure segmentation of 12 CS was completed using a novel hybrid MR/computed tomography (CT) atlas method and was improved upon using a 3-dimensional neural network (U-Net) from deep learning. Intra-fraction motion due to respiration was then quantified. The inter-fraction setup …


A Multimodal Approach To Investigate Brain Reorganization After Spinal Cord Injury Using Functional Magnetic Resonance Imaging And Functional Near-Infrared Spectroscopy, Keerthana Deepti Karunakaran May 2019

A Multimodal Approach To Investigate Brain Reorganization After Spinal Cord Injury Using Functional Magnetic Resonance Imaging And Functional Near-Infrared Spectroscopy, Keerthana Deepti Karunakaran

Dissertations

Traumatic Spinal Cord Injury (SCI) results in structural and functional neurological changes at both the brain and the level of the spinal cord. Anatomical studies indicate decreased grey matter volume in sensorimotor and non-sensorimotor regions of the cortex following SCI; whereas, neurophysiological findings mostly report altered functional activity in the sensorimotor nodes of the cortex, subcortex, and cerebellum. Therefore, it is currently unknown whether tissue atrophy observed in non-motor related areas has any concomitant functional consequences. Furthermore, the neural underpinnings of adaptive neuroplasticity after SCI is not well-defined in the current literature. Hence, this dissertation is a pioneer study investigating …


Study Of Mri Signal In The Presence Of Discrete Spherical Magnetic Particles, Paul Kokeny Jan 2018

Study Of Mri Signal In The Presence Of Discrete Spherical Magnetic Particles, Paul Kokeny

Wayne State University Dissertations

Simulating signal behavior in Magnetic Resonance imaging (MRI) is often a necessary step in being able to understand how signal relates to certain physiological parameters. One such parameter of interest in the body is magnetic susceptibility since it is related to iron content. The bulk magnetic susceptibility of an object is a property that describes how magnetized it becomes when placed in an external magnetic field. When the bulk susceptibility of an object arises from the presence of discrete magnetic inclusions, the MRI phase signal inside the object can no longer be determined analytically by assuming it has a continuous …


Computer-Aided Diagnoses (Cad) System: An Artificial Neural Network Approach To Mri Analysis And Diagnosis Of Alzheimer's Disease (Ad), Berizohar Padilla Cerezo Dec 2017

Computer-Aided Diagnoses (Cad) System: An Artificial Neural Network Approach To Mri Analysis And Diagnosis Of Alzheimer's Disease (Ad), Berizohar Padilla Cerezo

Master's Theses

Alzheimer’s disease (AD) is a chronic and progressive, irreversible syndrome that deteriorates the cognitive functions. Official death certificates of 2013 reported 84,767 deaths from Alzheimer’s disease, making it the 6th leading cause of death in the United States. The rate of AD is estimated to double by 2050. The neurodegeneration of AD occurs decades before symptoms of dementia are evident. Therefore, having an efficient methodology for the early and proper diagnosis can lead to more effective treatments.

Neuroimaging techniques such as magnetic resonance imaging (MRI) can detect changes in the brain of living subjects. Moreover, medical imaging techniques are the …


Computer-Assisted Characterization Of Prostate Cancer On Magnetic Resonance Imaging, Derek J. Soetemans Mar 2017

Computer-Assisted Characterization Of Prostate Cancer On Magnetic Resonance Imaging, Derek J. Soetemans

Electronic Thesis and Dissertation Repository

Prostate cancer (PCa) is one of the most prevalent cancers among men. Early diagnosis can improve survival and reduce treatment costs. Current inter-radiologist variability for detection of PCa is high. The use of multi-parametric magnetic resonance imaging (mpMRI) with machine learning algorithms has been investigated both for improving PCa detection and for PCa diagnosis. Widespread clinical implementation of computer-assisted PCa lesion characterization remains elusive; critically needed is a model that is validated against a histologic reference standard that is densely sampled in an unbiased fashion. We address this using our technique for highly accurate fusion of mpMRI with whole-mount …


A Structural And Functional Analysis Of Human Brain Mri With Attention Deficit Hyperactivity Disorder, Arjun A. Watane Jan 2017

A Structural And Functional Analysis Of Human Brain Mri With Attention Deficit Hyperactivity Disorder, Arjun A. Watane

Honors Undergraduate Theses

Attention Deficit Hyperactivity Disorder (ADHD) affects 5-10% of children worldwide. Its effects are mainly behavioral, manifesting in symptoms such as inattention, hyperactivity, and impulsivity. If not monitored and treated, ADHD may adversely affect a child's health, education, and social life. Furthermore, the neurological disorder is currently diagnosed through interviews and opinions of teachers, parents, and physicians. Because this is a subjective method of identifying ADHD, it is easily prone to error and misdiagnosis. Therefore, there is a clear need to develop an objective diagnostic method for ADHD.

The focus of this study is to explore the use of machine language …


Toward Magnetic Resonance Only Treatment Planning: Distortion Mitigation And Image-Guided Radiation Therapy Validation, Ryan Glen Price Jan 2016

Toward Magnetic Resonance Only Treatment Planning: Distortion Mitigation And Image-Guided Radiation Therapy Validation, Ryan Glen Price

Wayne State University Dissertations

While MR-only treatment planning has shown promise, there are still several well-known challenges that are currently limiting widespread clinical implementation.

Firstly, MR images are affected by both patient-induced and system-level geometric distortions that can significantly degrade treatment planning accuracy. . In addition, the availability of comprehensive distortion analysis software is currently limited. Also while many groups have been working toward a synthetic CT solution, further study is needed on the implementation of synCTs as the reference datasets for linac-based image-guided radiation therapy (IGRT) to help determine their robustness in an MR-only workflow.

A 36×43×2 cm3 phantom with 255 known landmarks …


Impact Of Acl Injury On Patellar Cartilage Thickness, Ethan Leveillee Jan 2016

Impact Of Acl Injury On Patellar Cartilage Thickness, Ethan Leveillee

Graduate College Dissertations and Theses

ACL injury has been shown to have long-lasting and severe consequences on the different structures of the knee such as the articular cartilage and meniscus. Cartilage thickness changes in particular are indicative of osteoarthritic changes in the tibiofemoral joint. While there has been significant research focused on cartilage changes of the tibia and femur, there has been little work looking at patellar cartilage. The following goals were set forth for this study. First, to establish a robust coordinate system to accurately determine the location and orientation of the patella. Secondly, to determine the effects of ACL injury on patellar cartilage …


Automated Segmentation Of Left And Right Ventricles In Mri And Classification Of The Myocarfium Abnormalities, Cyrus (Mohammad Saleh) Nambakhsh Sep 2013

Automated Segmentation Of Left And Right Ventricles In Mri And Classification Of The Myocarfium Abnormalities, Cyrus (Mohammad Saleh) Nambakhsh

Electronic Thesis and Dissertation Repository

A fundamental step in diagnosis of cardiovascular diseases, automated left and right ventricle (LV and RV) segmentation in cardiac magnetic resonance images (MRI) is still acknowledged to be a difficult problem. Although algorithms for LV segmentation do exist, they require either extensive training or intensive user inputs. RV segmentation in MRI has yet to be solved and is still acknowledged a completely unsolved problem because its shape is not symmetric and circular, its deformations are complex and varies extensively over the cardiac phases, and it includes papillary muscles. In this thesis, I investigate fast detection of the LV endo- and …