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3D Vessel Segmentation and Its Applications
PhD Thesis Proposal Defence
Title: "3D Vessel 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
proposal, 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 is
evaluated on public evaluation system and proved 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 proposal, two segmentation and feature
based methods (PWIS and type-based) and one learning based stenosis
detection method is proposed and evaluated to be effective in improving
the stenoses detection rates.
Date: Tueesday, 20 May 2014
Time: 10:00am - 12:00noon
Venue: Room 4480
lifts 25/26
Committee Members: Dr. Albert Chung (Supervisor)
Prof. Chiew-Lan Tai (Chairperson)
Prof. Dit-Yan Yeung
Dr. Weichuan Yu (ECE)
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