DocumentCode
2918706
Title
Novel 4-D Open-Curve Active Contour and curve completion approach for automated tree structure extraction
Author
Wang, Yu ; Narayanaswamy, Arunachalam ; Roysam, Badrinath
Author_Institution
Rensselaer Polytech. Inst., Troy, NY, USA
fYear
2011
fDate
20-25 June 2011
Firstpage
1105
Lastpage
1112
Abstract
We present novel approaches for fully automated extraction of tree-like tubular structures from 3-D image stacks. A 4-D Open-Curve Active Contour (Snake) model is proposed for simultaneous 3-D centerline tracing and local radius estimation. An image energy term, stretching term, and a novel region-based radial energy term constitute the energy to be minimized. This combination of energy terms allows the 4-D open-curve snake model, starting from an automatically detected seed point, to stretch along and fit the tubular structures like neurites and blood vessels. A graph-based curve completion approach is proposed to merge possible fragments caused by discontinuities in the tree structures. After tree structure extraction, the centerlines serve as the starting points for a Fast Marching segmentation for which the stopping time is automatically chosen. We illustrate the performance of our method with various datasets.
Keywords
feature extraction; image segmentation; solid modelling; 3-D centerline tracing; 3-D image stacks; 4-D open-curve active contour model; 4-D open-curve snake model; automated tree structure extraction; automatic seed point detection; blood vessels; fast marching segmentation; graph-based curve completion approach; image energy term; local radius estimation; region-based radial energy term; Active contours; Estimation; Force; Head; Image segmentation; Mathematical model; Solid modeling;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on
Conference_Location
Providence, RI
ISSN
1063-6919
Print_ISBN
978-1-4577-0394-2
Type
conf
DOI
10.1109/CVPR.2011.5995620
Filename
5995620
Link To Document