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Articles

A novel level set method for image segmentation by combining local and global information

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Pages 2399-2412 | Received 14 Feb 2017, Accepted 17 Jul 2017, Published online: 28 Aug 2017

References

  • Kass, W.; Witkin, A.; Terzopoulos, D. Snakes: Active Contour Models. Int. J. Comput. Vision 1988, 1, 312–331.
  • Caselles, V.; Kimmel, R.; Sapiro, G. Geodesic Active Contours. Int. J. Comput. Vision 1997, 22, 61–79.
  • Li, C.; Xu, C.; Gui, C.; Fox, M.D. Distance Regularized Level Set Evolution and its Application to Image Segmentation. IEEE Trans. Image Process. 2010, 19, 430–436.
  • Paragios, N.; Deriche, R. Geodesic Active Regions and Level Set Methods for Supervised Texture Segmentation. Int. J. Comput. Vision 2002, 46, 223–247.
  • Chan, T.; Vese, L. Active contours without edges. IEEE Trans. Image Process. 2001, 10, 266–77.
  • Li, C.; Huang, R.; Ding, Z.H.; Gatenby, C.; Metaxas, D.; Gore, J. A Variational Level Set Approach to Segmentation and Bias Correction of Images with Intensity Inhomogeneity. IEEE Trans. Image Process. 2011, 20, 2007–2016.
  • Mille, J. Narrow Band Region-based Active Contours and Surfaces for 2D and 3D Segmentation. Comput. Vision Image Understanding 2009, 113, 946–965.
  • Li, C.; Xu, C.; Anderson, A.W.; Gore, J.C. MRI Tissue Classification and Bias Field Estimation Based on Coherent Local Intensity Clustering: A Unified Energy Minimization Framework. In Proceedings of the 21st International Conference on Information Processing in Medical Imaging (IPMI’09); LNCS, Vol. 5636; Williamsburg, VA, 2009; pp 288–299.
  • Yu, C.; Zhang, W.; Yu, Y.; Li, Y. A Novel Active Contour Model for Image Segmentation Using Distance Regularization Term. Comput. Math. Appl. 2013, 65, 1746–1759.
  • Wang, X.; Min, H.; Zhang, Y. Multi-scale Local Region Based Level Set Method for Image Segmentation in the Presence of Intensity Inhomogeneity. Neurocomputing 2015, 151, 1086–1098.
  • Mumford, D.; Shah, J. Optimal Approximation by Piecewise Smooth Functions and Associated Variational Problems. Commun. Pure Appl. Math. 1989, 42, 577–685.
  • Li, C.; Kao, C.; Gore, J.; Ding, Z. Implicit Active Contours Driven by Local Binary Fitting Energy. IEEE Conference on Computer Vision and Pattern Recognition(CVPR); Washington, DC, USA, IEEE Computer Society, 2007; pp 1–7.
  • Zhang, K.; Zhang, L.; Song, H.; Zhou, W. Active contours with selective local or global segmentation: A new formulation and level set method. Image Vision Comput. 2010, 28, 668–676.
  • Wang, X.; Huang, D.; Xu, H. An Efficient Local Chan-Vese Model for Image Segmentation. Pattern Recogn. 2010, 43, 603–618.
  • Ji, Z.; Xia, Y.; Sun, Q.; Cao, G.; Chen, Q. Active Contours Driven by Local Likelihood Image Fitting Energy for Image Segmentation. Inf. Sci. 2015, 301, 285–304.
  • Yu, Y.; Zhang, C.; Wei, Y.; Li, X. Active Contour Method Combining Local Fitting Energy and Global Fitting Energy Dynamically; LNCS, Vol. 6165; ICMB: Hong Kong, China, 2010; pp 163–172.
  • Tian, Y.; Duan, F.; Zhou, M.; Wu, Z. Active Contour Model Combining Region and Edge Information. Mach. Vision Appl. 2013, 24, 47–61.
  • Li, D.; Li, W.; Liao, Q. Active Contours Driven by Local and Global Probability Distributions. J. Vision Commun. Image R. 2013, 24, 522–533.
  • Wang, H.; Huang, T.Z.; Xu, Z.; Wang, Y. An Active Contour Model and its Algorithms with Local and Global Gaussian Distribution Fitting Energies. Inf. Sci. 2014, 263, 43–59.
  • Wang, X.F.; Min, H.; Zou, L.; Zhang, Y.G. A Novel Level Set Method for Image Segmentation by Incorporating Local Statistical Analysis and Global Similarity Measurement. Pattern Recogn. 2015, 48, 189–204.
  • Ali, H.; Badshah, N.; Chen, K.; AliKhan, G. A Variational Model with Hybrid Images Data Fitting Energies for Segmentation of Images with Intensity Inhomogeneity. Pattern Recogn. 2016, 51, 27–42.
  • Wang, L.; Li, C.; Suna, Q.; Xia, D.; Kao, C. Active Contours Driven by Local and Global Intensity Fitting Energy with Application to Brain MR Image Segmentation. Comput. Med. Imaging Graph. 2009, 33, 520–531.
  • Dong, F.; Chen, Z.; Wang, J. A New Level Set Method for Inhomogeneous Image Segmentation. Image Vision Comput. 2013, 31, 809–822.
  • Osher, S.; Fedkiw, R. Level Set Methods and Dynamic Implicit Surfaces; Springer-Verlag, New York, 2002.
  • Perona, P.; Malik, J. Scale-space and Edge Detection Using Anisotropic Diffusion. IEEE Trans. Pattern Anal. Mach. Intell. 1990, 12, 629–640.

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