Graph-based 3D Vascular Segmentation and Its Applications

The Hong Kong University of Science and Technology
Department of Computer Science and Engineering


PhD Thesis Defence


Title: "Graph-based 3D Vascular Segmentation and Its Applications"

By

Miss Ning ZHU


Abstract

In recent years, vessel disease, which is one of the major causes of death 
around the world, has become an important health problem. Vessel 
segmentation is an important technique, and it can help the diagnosis, 
visualization, treatment and surgery planning for vessel diseases. In this 
thesis, we first review existing techniques for 3D vessel segmentation. 
Then several vessel segmentation techniques including centerline detection 
method (Minimum Average-cost Path for 4D Optimization), centerline-based 
segmentation methods (Optimal Cross Sections and Graph Optimization via 
graph cuts) and segmentation methods without ROI restriction (Random Walks 
with ACF, Random Walk based CEDA Optimization, Power-watershed based 
Optimization with TMT, Single Target Segmentation with AP-TMT) are 
proposed. Among these methods, Random Walk based CEDA Optimization has 
been evaluated on public evaluation system and demonstrated to be more 
accurate than all state-of-the-art methods on segmentation accuracy for 
healthy vessels. As for diseased vessel parts, comparable results are 
obtained. Vessel stenosis is one major type of vascular diseases. Because 
of the complex structure of stenoses, both detection and quantification of 
stenoses are challenging. In this thesis, two segmentation and feature 
based methods (PWIS and type-based) and one learning based stenosis 
detection method is proposed and evaluated to be effective on improving 
the stenosis detection rates.


Date:			Tuesday, 19 August 2014

Time:			10:00am - 12:00noon

Venue:			Room 4472
 			Lifts 25/26

Chairman:		Prof. Ying Chau (CBME)

Committee Members:	Prof. Albert Chung (Supervisor)
 			Prof. Chiew-Lan Tai
 			Prof. Dit-Yan Yeung
 			Prof. Weichuan Yu (ECE)
 			Prof. Pheng-Ann Heng (Comp. Sci. & Engg., CUHK)


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