Department
of Computer Science
In partial fulfillment of the
requirements for the degree of
Doctor of Philosophy
Uday Kurkure
will defend his dissertation
Computational
Methods for
Non-Invasive Cardiovascular Image Analysis
Abstract
Non-invasive cardiovascular imaging
has found significant utility for extraction of relevant quantitative
descriptors of clinical importance for cardiovascular risk prediction and
diagnosis. Magnetic resonance imaging (MRI) has been the preferred modality for
evaluation of left ventricular function and structure, whereas computed
tomography (CT) has been used extensively for coronary artery calcification
analysis. However, in clinical practice, the analysis of these images is
performed manually, which is tedious, prone to human error and becomes
prohibitive with the large amount of data being produced. This dissertation
presents a novel multi-class multi-feature fuzzy connectedness method to
segment objects with complex appearance and background. In addition, novel
computational methods for automated segmentation of the left ventricle and
detection of the coronary calcifications from the MRI and CT images,
respectively, are presented. Since our results are comparable with those of
human experts and demonstrate the possibility of fully automatic analysis of
left ventricular functioning and coronary artery calcification, they pave the
way for employing automated methods to analyze massive amounts of data from a
population screening regimen.
Date: Tuesday, April
22, 2008
Time: 10:00 AM
Place: 550-PGH
Faculty, students, and the general public are invited.
Advisor: Prof. Ioannis A. Kakadiaris