ML Anthology

Deformable Boundary Finding Influenced by Region Homogeneity

Amit Chakraborty, Lawrence H. Staib, James S. Duncan
CVPR 1994 pp. 624-627
doi:10.1109/CVPR.1994.323790 /cvpr/1994/chakraborty1994cvpr-deformable/

Abstract

Accurately segmenting and quantifying structures is a key issue in biomedical image analysis. The two conventional methods of image segmentation, region-based segmentation and boundary finding, often suffer from a variety of limitations. We propose a method which endeavors to integrate the two approaches in an effort to form a unified approach that is robust to noise and poor initialization. Our approach uses Green's theorem to derive the boundary of a homogeneous region-classified area in the image and integrates this with a grey-level-gradient-based boundary finder. This combines the perceptual notions of edge/shape information with gray level homogeneity.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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Text

Chakraborty et al. "Deformable Boundary Finding Influenced by Region Homogeneity." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1994. doi:10.1109/CVPR.1994.323790

Markdown

[Chakraborty et al. "Deformable Boundary Finding Influenced by Region Homogeneity." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1994.](https://mlanthology.org/cvpr/1994/chakraborty1994cvpr-deformable/) doi:10.1109/CVPR.1994.323790

BibTeX

@inproceedings{chakraborty1994cvpr-deformable,
  title     = {{Deformable Boundary Finding Influenced by Region Homogeneity}},
  author    = {Chakraborty, Amit and Staib, Lawrence H. and Duncan, James S.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1994},
  pages     = {624-627},
  doi       = {10.1109/CVPR.1994.323790},
  url       = {https://mlanthology.org/cvpr/1994/chakraborty1994cvpr-deformable/}
}