Novel 4-D Open-Curve Active Contour and Curve Completion Approach for Automated Tree Structure Extraction
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.
Cite
Text
Wang et al. "Novel 4-D Open-Curve Active Contour and Curve Completion Approach for Automated Tree Structure Extraction." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2011. doi:10.1109/CVPR.2011.5995620Markdown
[Wang et al. "Novel 4-D Open-Curve Active Contour and Curve Completion Approach for Automated Tree Structure Extraction." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2011.](https://mlanthology.org/cvpr/2011/wang2011cvpr-novel/) doi:10.1109/CVPR.2011.5995620BibTeX
@inproceedings{wang2011cvpr-novel,
title = {{Novel 4-D Open-Curve Active Contour and Curve Completion Approach for Automated Tree Structure Extraction}},
author = {Wang, Yu and Narayanaswamy, Arunachalam and Roysam, Badrinath},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year = {2011},
pages = {1105-1112},
doi = {10.1109/CVPR.2011.5995620},
url = {https://mlanthology.org/cvpr/2011/wang2011cvpr-novel/}
}