The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
Active contours with selective local or global segmentation: A new formulation and level set method
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Citations
Cites
Kass, M., Witkin, A., & Terzopoulos, D. (1988) · International Journal of Computer Vision · doi:10.1007/bf00133570 · Cited by 17,070
Scale-space and edge detection using anisotropic diffusion
Perona, P., & Malik, J. (1990) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.56205 · Cited by 12,119
Chan, T. F., & Vese, L. A. (2001) · IEEE Transactions on Image Processing · doi:10.1109/83.902291 · Cited by 10,304
Caselles, V., Kimmel, R., & Sapiro, G. (1997) · International Journal of Computer Vision · doi:10.1023/a:1007979827043 · Cited by 5,244
Optimal approximations by piecewise smooth functions and associated variational problems
Mumford, D., & Shah, J. (1989) · Communications on Pure and Applied Mathematics · doi:10.1002/cpa.3160420503 · Cited by 5,208
Level Set Methods and Dynamic Implicit Surfaces
Osher, S., & Fedkiw, R. (2003) · Applied Mathematical Sciences · doi:10.1007/b98879 · Cited by 4,951
Snakes, shapes, and gradient vector flow
Xu, C., & Prince, J. L. (1998) · IEEE Transactions on Image Processing · doi:10.1109/83.661186 · Cited by 4,001
A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model
Vese, L. A., & Chan, T. F. (2002) · International Journal of Computer Vision · doi:10.1023/a:1020874308076 · Cited by 2,384
Level Set Evolution without Re-Initialization: A New Variational Formulation
Li, C., Xu, C., Gui, C., & Fox, M. D. (2005) · 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) · doi:10.1109/cvpr.2005.213 · Cited by 1,783
Minimization of Region-Scalable Fitting Energy for Image Segmentation
Li, C., Kao, C.-Y., Gore, J. C., & Ding, Z. (2008) · IEEE Transactions on Image Processing · doi:10.1109/tip.2008.2002304 · Cited by 1,721
Cited by
A Level Set Approach to Image Segmentation With Intensity Inhomogeneity
Zhang, K., Zhang, L., Lam, K.-M., & Zhang, D. (2016) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2015.2409119 · Cited by 408
Self-citationAn active contour model based on local fitted images for image segmentation
Wang, L., Chang, Y., Wang, H., Wu, Z., Pu, J., & Yang, X. (2017) · Information Sciences · doi:10.1016/j.ins.2017.06.042 · Cited by 127
SuRVoS: Super-Region Volume Segmentation workbench
Luengo, I., Darrow, M. C., Spink, M. C., Sun, Y., Dai, W., He, C. Y., Chiu, W., Pridmore, T., Ashton, A. W., Duke, E. M. H., et al. (2017) · Journal of Structural Biology · doi:10.1016/j.jsb.2017.02.007 · Cited by 89
Metadata
- Authors
- Zhang, K., Zhang, L., Song, H., & Zhou, W.
- Venue
- Image and Vision Computing
- Publisher
- Elsevier BV
- Published
- 2010-04
- Volume
- 28
- Issue
- 4
- Pages
- 668-676
- ISSN
- 0262-8856 (ISSN-L)
- OpenAlex
- W2167354555
- Cited by
- 731
- References
- 24
- FWCI
- 27.12
- Type
- journal article
- Language
- en
- Open access
- closed
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- Zhang, K., Zhang, L., Song, H., & Zhou, W. (2010). Active contours with selective local or global segmentation: A new formulation and level set method. Image and Vision Computing. https://doi.org/10.1016/j.imavis.2009.10.009
Data sources
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.
