Biomedical Commons^™

Evaluating Algorithms Used For Fetal Brain Scan Segmentation, Connor Stewart Burgess

Undergraduate Student Research Internships Conference

The goal for this project was to successfully segment a fetal brain scan (fetal scan) using the algorithms provided by the program Slicer3D. To better understand the hurdles that arose when segmenting a fetal scan, we first look at the segmentation of an adult brain scan. This will allow us to see the straightforward nature of a brain segmentation when a high quality, high resolution volume with distinct structures is available. After examining the adult brain scan, attention will be moved to the segmentation of the fetal scan, where we’ll first look at the algorithms used and methods followed. Finally …

Deep Neural Network Analysis Of Pathology Images With Integrated Molecular Data For Enhanced Glioma Classification And Grading, Linmin Pei, Karra A. Jones, Zeina A. Shboul, James Y. Chen, Khan M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Gliomas are primary brain tumors that originate from glial cells. Classification and grading of these tumors is critical to prognosis and treatment planning. The current criteria for glioma classification in central nervous system (CNS) was introduced by World Health Organization (WHO) in 2016. This criteria for glioma classification requires the integration of histology with genomics. In 2017, the Consortium to Inform Molecular and Practical Approaches to CNS Tumor Taxonomy (cIMPACT-NOW) was established to provide up-to-date recommendations for CNS tumor classification, which in turn the WHO is expected to adopt in its upcoming edition. In this work, we propose a novel …

Automatic Signal And Image-Based Assessments Of Spinal Cord Injury And Treatments., Samineh Mesbah

Electronic Theses and Dissertations

Spinal cord injury (SCI) is one of the most common sources of motor disabilities in humans that often deeply impact the quality of life in individuals with severe and chronic SCI. In this dissertation, we have developed advanced engineering tools to address three distinct problems that researchers, clinicians and patients are facing in SCI research. Particularly, we have proposed a fully automated stochastic framework to quantify the effects of SCI on muscle size and adipose tissue distribution in skeletal muscles by volumetric segmentation of 3-D MRI scans in individuals with chronic SCI as well as non-disabled individuals. We also developed …

Multimodal Imaging For Enhanced Diagnosis And For Assessing Progression Of Alzheimer’S Disease, Chunfei Li

FIU Electronic Theses and Dissertations

A neuroimaging feature extraction model is designed to extract region-based image features whose values are predicted by base learners trained on raw neuroimaging morphological variables. The main objectives are to identify Alzheimer’s disease (AD) in its earliest manifestations, and be able to predict and gauge progression of the disease through the stages of mild cognitive impairment (EMCI), late MCI (LMCI) and AD. The model was evaluated on the ADNI database and showed 75.26% accuracy for the challenging EMCI diagnosis based on the 10-fold cross-validation. Our approach also performed well for the other binary classifications: EMCI vs. LMCI (72.3%), EMCI vs. …

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 …

An Integrated Multi-Modal Registration Technique For Medical Imaging, Xue Wang

FIU Electronic Theses and Dissertations

Registration of medical imaging is essential for aligning in time and space different modalities and hence consolidating their strengths for enhanced diagnosis and for the effective planning of treatment or therapeutic interventions. The primary objective of this study is to develop an integrated registration method that is effective for registering both brain and whole-body images. We seek in the proposed method to combine in one setting the excellent registration results that FMRIB Software Library (FSL) produces with brain images and the excellent results of Statistical Parametric Mapping (SPM) when registering whole-body images. To assess attainment of these objectives, the following …

Gui For Mri-Compatible Neural Stimulator And Recorder, Soo Han Soon, Nishant Babaria, Ranajay Mandal, Zhongming Liu

The Summer Undergraduate Research Fellowship (SURF) Symposium

Functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) are useful tools to analyze brain activities given active stimulation. However, the electromagnetic noise from the MRI distorts the brain signal recording and damages the subject with excessive heat generated on the electrodes attached to the skin. MRI-compatible recording and stimulation systems previously developed at LIBI lab were capable of removing the electromagnetic noise during the imaging process. Previously, the hardware systems had required the integrative software that could control both circuits simultaneously and enable users to easily change recording and stimulation parameters. Graphical user interface (GUI) programmed with computer language informed …

A Magnetic Resonance Compatible Knee Extension Ergometer, Youssef Jaber

Masters Theses

The product of this thesis aims to enable the study of the biochemical and physical dynamics of the lower limbs at high levels of muscle tension and fast contraction speeds. This is accomplished in part by a magnetic resonance (MR) compatible ergometer designed to apply a load as a torque of up to 420 Nm acting against knee extension at speeds as high as 4.7 rad/s. The system can also be adapted to apply the load as a force of up to 1200 N acting against full leg extension. The ergometer is designed to enable the use of magnetic resonance …

Interactive Visualization Of Multimodal Brain Connectivity: Applications In Clinical And Cognitive Neuroscience, Saeed Mahdizadeh Bakhshmand

Electronic Thesis and Dissertation Repository

Magnetic resonance imaging (MRI) has become a readily available prognostic and diagnostic method, providing invaluable information for the clinical treatment of neurological diseases. Multimodal neuroimaging allows integration of complementary data from various aspects such as functional and anatomical properties; thus, it has the potential to overcome the limitations of each individual modality. Specifically, functional and diffusion MRI are two non-invasive neuroimaging techniques customized to capture brain activity and microstructural properties, respectively. Data from these two modalities is inherently complex, and interactive visualization can assist with data comprehension.

The current thesis presents the design, development, and validation of visualization and computation …

Respiratory Prediction And Image Quality Improvement Of 4d Cone Beam Ct And Mri For Lung Tumor Treatments, Seonyeong Park

Theses and Dissertations

Identification of accurate tumor location and shape is highly important in lung cancer radiotherapy, to improve the treatment quality by reducing dose delivery errors. Because a lung tumor moves with the patient's respiration, breathing motion should be correctly analyzed and predicted during the treatment for prevention of tumor miss or undesirable treatment toxicity. Besides, in Image-Guided Radiation Therapy (IGRT), the tumor motion causes difficulties not only in delivering accurate dose, but also in assuring superior quality of imaging techniques such as four-dimensional (4D) Cone Beam Computed Tomography (CBCT) and 4D Magnetic Resonance Imaging (MRI). Specifically, 4D CBCT used in CBCT …

Breast Cancer Classification Of Mammographic Masses Using Circularity Max Metric, A New Method, Tae Keun Heo

Electronic Theses and Dissertations

Breast cancer classification can be divided into two categories. The first category is a benign tumor, and the other is a malignant tumor. The main purpose of breast cancer classification is to classify abnormalities into benign or malignant classes and thus help physicians with further analysis by minimizing potential errors that can be made by fatigued or inexperienced physicians. This paper proposes a new shape metric based on the area ratio of a circle to classify mammographic images into benign and malignant class. Support Vector Machine is used as a machine learning tool for training and classification purposes. The improved …

Effects Of Blood Flow On The Heating Of Cardiac Stents Due To Radio Frequency Fields, Nate Ian Elder

Open Access Theses

A safety concern during MRI scans with implanted medical devices is heating induced by the incident RF field. This research was performed to better understand the heating of cardiac stents during MRI. Heating of cardiac stents tends to occur at their ends. The temperature rise will be affected by blood flow through the lumen of the stent. In this work, an experiment was performed to simulate heating of a cardiac stent in the presence of blood flow during exposure to the electric field induced by a 64 MHz magnetic field, which corresponds to MRI at 1.5 T. The test procedure …

Sar Map Of Gel Phantom In A 64mhz Mri Birdcage By Fiber-Optic Thermometry And Fdtd Simulation, Chirag Mukesh Patel

Master's Theses

As implantable medical devices are being used more often to treat medical problems for which pharmaceuticals don’t suffice, it is important to understand their interactions with commonly used medical modalities. The interactions between medical implants and Magnetic Resonance Imaging machines have proven to be a risk for patients with implants.

Implanted medical devices with elongated metallic components can create harmful levels of local heating in a Magnetic Resonance Imaging (MRI) environment [1]. The heating of a biological medium under MRI is monitored via the Specific Absorption Rate (SAR). SAR, defined as power absorbed per unit mass (W/kg), can be calculated …