Fast Skeletonization of Blood Vessels
Open Access
- Author:
- Croasmun, Aaron Alan
- Graduate Program:
- Computer Science
- Degree:
- Master of Science
- Document Type:
- Master Thesis
- Date of Defense:
- October 05, 2012
- Committee Members:
- Sukmoon Chang, Thesis Advisor/Co-Advisor
Thang Nguyen Bui, Thesis Advisor/Co-Advisor
Linda Marie Null, Thesis Advisor/Co-Advisor
Jeremy Joseph Blum, Thesis Advisor/Co-Advisor
Omar A El Ariss, Thesis Advisor/Co-Advisor - Keywords:
- skeletonization
vascular network - Abstract:
- The study of the morphological and rheological behaviors of intramural vessels plays a critical role in various clinical applications such as surgical planning and radiotherapy. To better understand the rheological behavior of vascular structures in relation to the network morphology, we must obtain the concrete measurements of the morphometric parameters of the vascular networks under various conditions. Morphometric parameters of the networks include vessel diameter, branching points, branch end points, branch length, and branching angles. Because of the complexity of blood vessel morphology, however, it is difficult to obtain accurate measurements. In this thesis, we present a novel and efficient method for skeletonization of intramural vessel networks. The proposed method automatically skeletonizes the vascular network in a given image and constructs a graph structure that represents the branching structures of the network. Since the method processes a given image as a whole, the multiple vascular networks present in the image are automatically detected and skeletonized simultaneously. Moreover, since the skeletons are represented as graph structures, various morphometric parameters can be obtained automatically. We present the promising results of the proposed method applied to the complex structure of retinal vessel networks.