Paper Info
Title
Intracranial aneurysm segmentation in 3D CT angiography: method and quantitative validation
Abstract
Accurately quantifying aneurysm shape parameters is of clinical importance, as it is an important factor in choosing the right treatment modality (i.e. coiling or clipping), in predicting rupture risk and operative risk and for pre-surgical planning. The first step in aneurysm quantification is to segment it from other structures that are present in the image. As manual segmentation is a tedious procedure and prone to inter-and intra-observer variability, there is a need for an automated method which is accurate and reproducible. In this paper a novel semi-automated method for segmenting aneurysms in Computed Tomography Angiography (CTA) data based on Geodesic Active Contours is presented and quantitatively evaluated. Three different image features are used to steer the level set to the boundary of the aneurysm, namely intensity, gradient magnitude and variance in intensity. The method requires minimum user interaction, i.e. clicking a single seed point inside the aneurysm which is used to estimate the vessel intensity distribution and to initialize the level set. The results show that the developed method is reproducible, and performs in the range of inter-observer variability in terms of accuracy.
Year
DOI
Venue
2010
10.1117/12.843674
Proceedings of SPIE
Keywords
Field
DocType
intracranial aneurysm,GAC,level set,segmentation,evaluation
Computer vision,Feature (computer vision),Segmentation,Computed tomography angiography,Level set,Aneurysm,Artificial intelligence,Gradient magnitude,Clipping (audio),Angiography,Physics
Conference
Volume
ISSN
Citations 
7623
0277-786X
8
PageRank 
References 
Authors
0.69
6
8
Name
Order
Citations
PageRank
azadeh firouzian181.03
Rashindra Manniesing222820.43
zwenneke flach380.69
Roelof Risselada4101.24
fop van kooten580.69
Miriam C J M Sturkenboom6353.67
A van der Lugt7261.95
Wiro J. Niessen83821380.78