Adaptive Segmentation Of Cardiovascular Vessels
- ASU Author/Contributor (non-ASU co-authors, if there are any, appear on document)
- Erik J. Cole (Creator)
- Institution
- Appalachian State University (ASU )
- Web Site: https://library.appstate.edu/
- Advisor
- Rahman Tashakkori
Abstract: Coronary collateral vessels may contribute to survival after myocardial infarction by providing blood to the cardiac muscle after coronary arterial occlusion. However, these vessels are not present in all people and can develop after infarction and in some cases they develop prior to infarction for reasons not fully understood. The goal of this thesis is to investigate the segmentation of coronary collateral vessels from micro-computed tomography (microCT) images of a mouse's heart. A problem limiting study of collateral vessels is the exceedingly small size and correspondingly low blood flow of these vessels, making the regions of interest (ROI) below the resolution of most imaging modalities. Segmentation of vessels is a challenge for all imaging modalities and organs. There is no standard algorithm or method that works for all images, therefore, a combination of multiple approaches were used to address this problem.
Adaptive Segmentation Of Cardiovascular Vessels
PDF (Portable Document Format)
1498 KB
Created on 1/9/2020
Views: 558
Additional Information
- Publication
- Thesis
- Cole, E. (2019). Adaptive Segmentation Of Cardiovascular Vessels. Unpublished Master’s Thesis. Appalachian State University, Boone, NC.
- Language: English
- Date: 2019
- Keywords
- Segmentation, Collateral vessels, Image Processing,
Filtering