ML Anthology

A Sobolev-Type Metric for Polar Active Contours

Maximilian Baust, Anthony J. Yezzi, Gözde B. Ünal, Nassir Navab
CVPR 2011 pp. 1017-1024
doi:10.1109/CVPR.2011.5995310 /cvpr/2011/baust2011cvpr-sobolev/

Abstract

Polar object representations have proven to be a powerful shape model for many medical as well as other computer vision applications, such as interactive image segmentation or tracking. Inspired by recent work on Sobolev active contours we derive a Sobolev-type function space for polar curves. This so-called polar space is endowed with a metric that allows us to favor origin translations and scale changes over smooth deformations of the curve. Moreover, the resulting curve flow inherits the coarse-to-fine behavior of Sobolev active contours and is thus very robust to local minima. These properties make the resulting polar active contours a powerful segmentation tool for many medical applications, such as cross-sectional vessel segmentation, aneurysm analysis, or cell tracking.

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Text

Baust et al. "A Sobolev-Type Metric for Polar Active Contours." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2011. doi:10.1109/CVPR.2011.5995310

Markdown

[Baust et al. "A Sobolev-Type Metric for Polar Active Contours." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2011.](https://mlanthology.org/cvpr/2011/baust2011cvpr-sobolev/) doi:10.1109/CVPR.2011.5995310

BibTeX

@inproceedings{baust2011cvpr-sobolev,
  title     = {{A Sobolev-Type Metric for Polar Active Contours}},
  author    = {Baust, Maximilian and Yezzi, Anthony J. and Ünal, Gözde B. and Navab, Nassir},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2011},
  pages     = {1017-1024},
  doi       = {10.1109/CVPR.2011.5995310},
  url       = {https://mlanthology.org/cvpr/2011/baust2011cvpr-sobolev/}
}