Image segmentation by shape particle filtering

@article{Bruijne2004ImageSB,
  title={Image segmentation by shape particle filtering},
  author={Marleen de Bruijne and Mads Nielsen},
  journal={Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.},
  year={2004},
  volume={3},
  pages={722-725 Vol.3}
}
Statistical appearance models are valuable tools in medical image segmentation. Current methods elegantly incorporate global shape and appearance, but cannot cope with local appearance variations and rely on an assumption of Gaussian gray value distribution. Furthermore, initialization near the optimal solution is required. We propose a shape inference method that is based on pixel classification, so that local and non-linear intensity variations are dealt with naturally, while a global shape… CONTINUE READING
Highly Cited
This paper has 71 citations. REVIEW CITATIONS

From This Paper

Figures, tables, and topics from this paper.

Citations

Publications citing this paper.
Showing 1-10 of 39 extracted citations

Eye Shape and Corners Detection in Periocular Images Using Particle Filters

2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) • 2016
View 1 Excerpt

MCMC Shape Sampling for Image Segmentation with Nonparametric Shape Priors

2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) • 2016
View 1 Excerpt

72 Citations

0510'03'06'10'14'18
Citations per Year
Semantic Scholar estimates that this publication has 72 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.
Showing 1-10 of 19 references

Active blobs: region-based, deformable appearance models

Computer Vision and Image Understanding • 2003
View 1 Excerpt

Mean Shift: A Robust Approach Toward Feature Space Analysis

IEEE Trans. Pattern Anal. Mach. Intell. • 2002
View 1 Excerpt

Moderating k-NN Classifiers

Pattern Analysis & Applications • 2002
View 1 Excerpt

Active Appearance Models

IEEE Trans. Pattern Anal. Mach. Intell. • 2001
View 1 Excerpt