The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Boundary finding with parametrically deformable models
Abstract
Segmentation using boundary finding is enhanced both by considering the boundary as a whole and by using model-based global shape information. The authors apply flexible constraints, in the form of a probabilistic deformable model, to the problem of segmenting natural 2-D objects whose diversity and irregularity of shape make them poorly represented in terms of fixed features or form. The parametric model is based on the elliptic Fourier decomposition of the boundary. Probability distributions on the parameters of the representation bias the model to a particular overall shape while allowing for deformations. Boundary finding is formulated as an optimization problem using a maximum a posteriori objective function. Results of the method applied to real and synthetic images are presented, including an evaluation of the dependence of the method on prior information and image quality.>
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Cites
A Mathematical Theory of Communication
Shannon, C. E. (1948) · Bell System Technical Journal · doi:10.1002/j.1538-7305.1948.tb01338.x · Cited by 88,486
The Representation and Matching of Pictorial Structures
Fischler, M. A., & Elschlager, R. A. (1973) · IEEE Transactions on Computers · doi:10.1109/t-c.1973.223602 · Cited by 1,322
Cited by
Cootes, T. F., Edwards, G. J., & Taylor, C. J. (2001) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.927467 · Cited by 5,409
Deformable models in medical image analysis: a survey
McInerney, T., & Terzopoulos, D. (1996) · Medical Image Analysis · doi:10.1016/s1361-8415(96)80007-7 · Cited by 1,913
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
Computational anatomy: an emerging discipline
Grenander, U., & Miller, M. I. (1998) · Quarterly of Applied Mathematics · doi:10.1090/qam/1668732 · Cited by 623
A Level-Set Approach to 3D Reconstruction from Range Data
Whitaker, R. T. (1998) · International Journal of Computer Vision · doi:10.1023/a:1008036829907 · Cited by 517
Metadata
- Authors
- Staib, L. H., & Duncan, J. S.
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 1992
- Volume
- 14
- Issue
- 11
- Pages
- 1061-1075
- ISSN
- 0162-8828 (ISSN-L)
- OpenAlex
- W2148107745
- Cited by
- 756
- References
- 2
- FWCI
- 17.02
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
