Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/28310
Title: Brain vasculature segmentation from magnetic resonance angiographic image
Authors: DORNOOSH ZONOOBI
Keywords: Vasculature Segmentation, MRA images, Geodesic Active Contours.
Issue Date: 31-Jan-2008
Source: DORNOOSH ZONOOBI (2008-01-31). Brain vasculature segmentation from magnetic resonance angiographic image. ScholarBank@NUS Repository.
Abstract: Precise segmentation of vasculature from three-dimensional (3D) magnetic resonance angiography (MRA) images plays an important role in image-guided neurosurgery, pre-operation planning and clinical analysis. Level sets based evolution algorithms are being widely applied to MRA data sets. Our objective is to develop an automated segmentation scheme to accurately extract vasculature of the brain, especially the thin vessels. Inspired by the intrinsic properties of MRA, we have proposed a scheme called the gradient compensated active contour (GCAC), which compensates for the low gradient near the edge of thin vesselsb contour. The GCAC, which is based on level sets, has been tested on both synthetic volumetric images and real 3D MRA images. Our experiments show that the introduced gradient compensation can facilitate more accurate segmentation of thin blood vessels.
URI: http://scholarbank.nus.edu.sg/handle/10635/28310
Appears in Collections:Master's Theses (Open)

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
main.pdf2.11 MBAdobe PDF

OPEN

NoneView/Download

Page view(s)

187
checked on Dec 11, 2017

Download(s)

157
checked on Dec 11, 2017

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.