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Adame Valero, I.M. (2007)

Automated segmentation of atherosclerotic arteries in MR Images

Doctoral Thesis
Accurate visualization and quantification of atherosclerosis in a non-invasive manner by means of MR is, nowadays, of high importance, not only regarding morphology but also composition of the atherosclerotic plaques. MR has proven to be capable of detecting early, subclinical vulnerable plaque. However, when the analysis of atherosclerosis is based on visual interpretation of the images or manually delineated structures, the outcome is often not reliable. The main objective of this thesis was to investigate novel image processing techniques to automatically quantify markers of the severity of atherosclerosis in a reproducible manner, by automatically outlining the boundaries of the blood vessel wall, lumen and plaque burden. Different algorithms have been developed and applied to different vascular beds (aorta and carotid arteries) proving to be versatile and powerful tools, that provide quantitative reproducible parameters. These new techniques have been validated in limited...Show moreAccurate visualization and quantification of atherosclerosis in a non-invasive manner by means of MR is, nowadays, of high importance, not only regarding morphology but also composition of the atherosclerotic plaques. MR has proven to be capable of detecting early, subclinical vulnerable plaque. However, when the analysis of atherosclerosis is based on visual interpretation of the images or manually delineated structures, the outcome is often not reliable. The main objective of this thesis was to investigate novel image processing techniques to automatically quantify markers of the severity of atherosclerosis in a reproducible manner, by automatically outlining the boundaries of the blood vessel wall, lumen and plaque burden. Different algorithms have been developed and applied to different vascular beds (aorta and carotid arteries) proving to be versatile and powerful tools, that provide quantitative reproducible parameters. These new techniques have been validated in limited populations, proving to be accurate and reproducible. They are, therefore, suitable to be further adapted and to be employed in the clinical vascular research. This assists the physician in making a diagnosis and identifying high-risk patients, who may benefit from treatment.Show less
Atherosclerosis
Carotid Arteries
Image processing
Magnetic Resonance
Model-based segmentation
Plaque Burden
Vessel Wall Imaging
All authors
Adame Valero, I.M.
Supervisor
Reiber, J.H.C.
Co-supervisor
Lelieveldt, B.P.F.; Geest, R.J. van der
Qualification
Doctor (dr.)
Awarding Institution
Leiden University Medical Center (LUMC), Leiden University
Date
2007-04-04
Title of host publication
ASCI dissertation series
Publisher
ASCI graduate school|Laboratory for Clinical en Experimental Image processing, Faculty of Medicine / Leiden University Medical Center (LUMC), Leiden University
ISBN (print)
9789090211145

Publication Series

Name
18

Funding

Sponsorship
Financial support for chapters 3-5 was provided by the Marie Curie Industry Host Fellowship (grant HPMI-CT-2002-00175). Chapter 5 was also supported by contracts N01-HC-95159, N01 HC 95162, and N01 HC 95168 from the National Heart, Lung, and Blood Institute. The research described in chapters 6 and 7 was financially supported by the Dutch Science Foundation (NWO), under an innovational research incentive grant nr. 016.026.017.