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Fat Suppression and Segmentation in Phase-Contrast MRI Flow Measurements

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abstract
Cardiovascular disease is the leading cause of death in the world, accounting for almost 50% percent of all deaths in both developed and developing countries. In the United States, 41% of total mortality from all causes is due to cardiovascular diseases. Of these deaths, about 50% is related to the coronary heart disease, a condition that includes myocardial infarction, ischemic heart disease, and angina pectoris (chest pain). X-ray angiography and Doppler ultrasound flow measurement via catheterization are the two invasive clinical tools used extensively in the diagnosis of coronary artery disease. Despite significant technical improvements in the medical field, there is no non-invasive test to diagnose and monitor this disease, yet. Recent developments in magnetic resonance imaging (MRI) enabled the utilization of this imaging modality as an extremely powerful cardiovascular imaging tool. For instance, magnetic resonance (MR) phase contrast (PC) imaging holds great potential as a non-invasive diagnostic tool by measuring the blood flow in coronary arteries. Unfortunately, artifacts in the resultant images as well as current limitations of the PC technique have hindered its acceptance in the medical community as an alternative to current invasive methods. The major problems in PC flow imaging are: tight temporal resolution requirements on image acquisition, and inaccurate segmentation of the vessel due to cardiac motion and signal from the neighboring structures. This proposal aims to improve the utilization of PC flow imaging technique as a diagnostic tool by addressing these problems and reducing, if not eliminating, the associated artifacts. The focus of the first part of this dissertation is the signal contamination from the neighboring structures. For coronary circulation, the neighboring structure is fat, and it surrounds the whole vasculature bed. Current methods of addressing the fat related artifacts and problems will be discussed. One of these methods, spatial-spectral excitation, is implemented for PC flow imaging with the temporal resolution requirements in mind. Efficiency of the proposed solution has been demonstrated via simulations, phantom measurements, and real data analysis. The second part of this thesis looks into the problems related with vessel segmentation. Accurate vessel segmentation is crucial for the success of PC imaging, as it not only decides which pixels should be included in the flow quantification, but also provides the scaling factor (vessel area) to obtain the average flow values. A segmentation method based on the deformable templates is implemented for vessel segmentation. The beauty of the method is that it incorporates human heuristic or common sense into the segmentation process. The algorithm expects a certain shape very much like a radiologist does before looking at an image. The proposed solution has been applied to the segmentation of the ascending aorta PC flow images, and its performance is compared to the expert manual analysis results.
subject
Coronary Flow
Deformable Templates
Fat Suppression
Magnetic Resonance
Segmentation
Spatial-Spectral
contributor
Bayram, Ersin (author)
ebayram@wfubmc.edu (authorEmail)
Robert J. Plemmons (committee chair)
Kerry M. Link (committee member)
Robert A. Kraft (committee member)
Peter Santago II (committee member)
Craig A. Hamilton (committee member)
creator
Bayram, Ersin
date
2008-09-28T10:53:00Z (accessioned)
2010-06-18T18:59:49Z (accessioned)
2004-12-21 (available)
2008-09-28T10:53:00Z (available)
2010-06-18T18:59:49Z (available)
2003-07-22 (issued)
degree
null (defenseDate)
Medical Engineering (discipline)
Wake Forest University (grantor)
PHD (level)
identifier
ersindissertation.pdf
http://hdl.handle.net/10339/14895 (uri)
migration
etd-10082003-135303 (oldETDId)
rights
Release the entire work immediately for access worldwide. (accessRights)
I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to Wake Forest University or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report. (license)
title
Fat Suppression and Segmentation in Phase-Contrast MRI Flow Measurements

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