The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Statistical shape influence in geodesic active contours
Abstract
A novel method of incorporating shape information into the image segmentation process is presented. We introduce a representation for deformable shapes and define a probability distribution over the variances of a set of training shapes. The segmentation process embeds an initial curve as the zero level set of a higher dimensional surface, and evolves the surface such that the zero level set converges on the boundary of the object to be segmented. At each step of the surface evolution, we estimate the maximum a posteriori (MAP) position and shape of the object in the image, based on the prior shape information and the image information. We then evolve the surface globally; towards the MAP estimate, and locally based on image gradients and curvature. Results are demonstrated on synthetic data and medical imagery in 2D min 3D.
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Cites
Turk, M., & Pentland, A. (1991) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.1991.3.1.71 · Cited by 13,733
Cited by
Ultrasound image segmentation: a survey
Noble, J. A., & Boukerroui, D. (2006) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2006.877092 · Cited by 1,157
A shape-based approach to the segmentation of medical imagery using level sets
Tsai, A., Yezzi, A., Wells, W., Tempany, C., Tucker, D., Fan, A., Grimson, W. E., & Willsky, A. (2003) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2002.808355 · Cited by 894
Self-citationShape Priors for Level Set Representations
Rousson, M., & Paragios, N. (2002) · Lecture Notes in Computer Science · doi:10.1007/3-540-47967-8_6 · Cited by 502
Using Prior Shapes in Geometric Active Contours in a Variational Framework
Chen, Y., Tagare, H. D., Thiruvenkadam, S., Huang, F., Wilson, D., Gopinath, K. S., Briggs, R. W., & Geiser, E. A. (2002) · International Journal of Computer Vision · doi:10.1023/a:1020878408985 · Cited by 406
Comparison of quantitative methods for cell‐shape analysis
PINCUS, Z., & THERIOT, J. A. (2007) · Journal of Microscopy · doi:10.1111/j.1365-2818.2007.01799.x · Cited by 288
Metadata
- Authors
- Leventon, M. E., Grimson, W. E. L., & Faugeras, O.
- Venue
- Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662)
- Publisher
- IEEE Comput. Soc
- Published
- 2002-11-07
- Volume
- 1
- Pages
- 316-323
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2167338900
- Cited by
- 1,141
- References
- 1
- FWCI
- 34.99
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Statistical shape influence in geodesic active contours. https://app.cochat.ai/papers/10.1109/cvpr.2000.855835
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- Leventon, M. E., Grimson, W. E. L., & Faugeras, O. (2002). Statistical shape influence in geodesic active contours. Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662). https://doi.org/10.1109/cvpr.2000.855835
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
