ML Anthology

Rational Discrete Generalized Cylinders and Their Application to Shape Recovery in Medical Images

James P. Williams, Lawrence B. Wolff, John K. Johnstone
CVPR 1997 pp. 387-392
doi:10.1109/CVPR.1997.609354 /cvpr/1997/williams1997cvpr-rational/

Abstract

Generalized cylinders (GCs) are a popular representational tool in computer vision. In medical imaging, the curved axis GC is particularly applicable to a number of elongated physical structures such as vasculature, bone and bronchi. In many of these instances, it is necessary to recover curved-axis GCs with arbitrary cross-sections. It is also vital that these structures, once recovered, can be analyzed and visualized with off-the-shelf algorithms and software packages. Such tools are usually designed to operate on the domain of polynomial or rational surfaces. Unfortunately most extant, suitably versatile GC representations do not admit rational parameterizations. We develop an entirely rational B-spline representation for generalized cylinders with curved axes and arbitrary cross-section functions. We demonstrate how our representation can be used as a deformable model by extracting a rational GC from pre-segmented spinal data using a discrete dynamic surface fit.

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Cite

Text

Williams et al. "Rational Discrete Generalized Cylinders and Their Application to Shape Recovery in Medical Images." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1997. doi:10.1109/CVPR.1997.609354

Markdown

[Williams et al. "Rational Discrete Generalized Cylinders and Their Application to Shape Recovery in Medical Images." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1997.](https://mlanthology.org/cvpr/1997/williams1997cvpr-rational/) doi:10.1109/CVPR.1997.609354

BibTeX

@inproceedings{williams1997cvpr-rational,
  title     = {{Rational Discrete Generalized Cylinders and Their Application to Shape Recovery in Medical Images}},
  author    = {Williams, James P. and Wolff, Lawrence B. and Johnstone, John K.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1997},
  pages     = {387-392},
  doi       = {10.1109/CVPR.1997.609354},
  url       = {https://mlanthology.org/cvpr/1997/williams1997cvpr-rational/}
}