INITIAL CONTOUR GENERATION APPROACH IN LEVEL SET METHODS FOR DENTAL IMAGE SEGMENTATION
DOI:
https://doi.org/10.11113/jt.v78.6921Keywords:
Segmentation, dental x-ray, initial contour, level set, binarizationAbstract
Segmentation is challenging process in medical images especially on dental x-ray images. Level set methods have best result on medical and dental image segmentation. Initial Contour (IC) is the essential step in level set methods to initialize the efficient process. However, the main issue with IC is how to generate the automatic technique in order to reduce the human interaction and produce accurate result. In this paper a new region-based technique for IC generation, is proposed to generate the most suitable IC. We have utilized the statistical and morphological information inside and outside the contour to establish a region-based map function. This function is able to find the suitable IC on images to perform by level set methods. Experiments on dental x-ray images demonstrate the robustness of segmentation process using proposed method even on noisy images and with weak boundary. Furthermore, computational cost of segmentation process is reduced.
References
Caselles, V., Catte, F., Coll, T., & Dibos, F. 1993. A Geometric Model For Active Contours In Image Processing. Numerische Mathematic. 66(1): 1-31.
Caselles, V., Kimmel, R., & Sapiro, G. 1997. Geodesic Active Contours. International Journal Of Computer Vision. 22(1): 61-79.
Chan, T. F., & Vese, L. A. 2001. Active Contours Without Edges. Image Processing, IEEE Transactions On. 10(2): 266-277.
Deng, J., & Tsui, H.-T. 2002. A Fast Level Set Method For Segmentation Of Low Contrast Noisy Biomedical Images. Pattern Recognition Letters. 23(1): 161-169.
Ehsani Rad, A., Mohd Rahim, M., Rehman, A., Altameem, A., & Saba, T. 2013. Evaluation of Current Dental Radiographs Segmentation Approaches in Computer-aided Applications. IETE Technical Review. 30(3): 210.
Fedkiw, S. O. 2003. Level Set Methods And Dynamic Implicit Surfaces.
Gao, H., & Chae, O. 2010. Individual Tooth Segmentation From CT Images Using Level Set Method With Shape And Intensity Prior. Pattern Recognition. 43(7): 2406-2417.
Jeon, M., Alexander, M., Pedrycz, W., & Pizzi, N. 2005. Unsupervised Hierarchical Image Segmentation With Level Set And Additive Operator Splitting. Pattern Recognition Letters. 26(10): 1461-1469.
Kass, M., Witkin, A., & Terzopoulos, D. 1988. Snakes: Active Contour Models. International Journal Of Computer Vision. 1(4): 321-331.
Kimia, B. B., Tannenbaum, A. R., & Zucker, S. W. 1995. Shapes, Shocks, And Deformations I: The Components Of Two-Dimensional Shape And The Reaction-Diffusion Space. International Journal Of Computer Vision. 15(3): 189-224.
Ma, W.-Y., & Manjunath, B. 1997. Edge Flow: A Framework Of Boundary Detection And Image Segmentation. Computer Vision and Pattern Recognition. Proceedings 1997 IEEE Computer Society Conference on. 744-749.
Malladi, R., Sethian, J. A., & Vemuri, B. C. 1995. Shape Modeling With Front Propagation: A Level Set Approach. Pattern Analysis and Machine Intelligence. IEEE Transactions on. 17(2): 158-175.
Mumford, D., & Shah, J. 1989. Optimal Approximations By Piecewise Smooth Functions And Associated Variational Problems. Communications On Pure And Applied Mathematics. 42(5): 577-685.
Nilsson, B., & Heyden, A. 2003. A Fast Algorithm For Level Set-Like Active Contours. Pattern Recognition Letters. 24(9): 1331-1337.
Osher, S., & Sethian, J. A. 1988. Fronts Propagating With Curvature-Dependent Speed: Algorithms Based On Hamilton-Jacobi Formulations. Journal Of Computational Physics. 79(1) 12-49.
Otsu, N. 1975. A Threshold Selection Method From Gray-Level Histograms. Automatica. 11(285-296): 23-27.
Peng, D., Merriman, B., Osher, S., Zhao, H., & Kang, M. 1999. A PDE-based Fast Local Level Set Method. Journal of Computational Physics. 155(2): 410-438.
Qu, Y., Wong, T.-T., & Heng, P. A. 2007. Image Segmentation Using The Level Set Method. In Deformable Models. Springer. 95-122.
Sethian, J. A. 2003. Level Set Methods And Fast Marching Methods. Journal of Computing and Information Technology. 11(1): 1-2.
Shuo, L., Fevens, T., Krzyzak, A., & Li, S. 2006. An Automatic Variational Level Set Segmentation Framework For Computer Aided Dental X-Rays Analysis In Clinical Environments. Computerized Medical Imaging and Graphics. 30(2): 65-74.
Shuo, L., Fevens, T., Krzyzak, A., Jin, C., & Li, S. 2007. Semi-automatic Computer Aided Lesion Detection In Dental X-Rays Using Variational Level Set. Pattern Recognition. 40(10): 2861-2873.
Weickert, J., & Kuhne, G. 2003. Fast Methods For Implicit Active Contour Models. In Geometric Level Set Methods In Imaging, Vision, And Graphics. Springer. 43-57.
Xie, X. 2010. Active Contouring Based On Gradient Vector Interaction And Constrained Level Set Diffusion. Image Processing, IEEE Transactions on. 19(1): 154-164.
Xie, X., & Mirmehdi, M. 2008. MAC: Magnetostatic Active Contour Model. Pattern Analysis and Machine Intelligence, IEEE Transactions on. 30(4): 632-646.
Xu, C., & Prince, J. L. 1998. Generalized Gradient Vector Flow External Forces For Active Contours. Signal Processing. 71(2): 131-139.
Xu, N., Ahuja, N., & Bansal, R. 2007. Object Segmentation Using Graph Cuts Based Active Contours. Computer Vision and Image Understanding. 107(3): 210-224.
Zhang, Y., Matuszewski, B. J., Shark, L., & Moore, C. J. 2008. Medical Image Segmentation Using New Hybrid Level-Set Method. BioMedical Visualization, 2008. MEDIVIS'08. Fifth International Conference. 71-76.
Ehsanirad, A. 2010. Plant Classification Based On Leaf Recognition. International Journal of Computer Science and Information Security. 8(4): 78-81.
Rad, A. E., Amin, I. B. M., Rahim, M. S. M., & Kolivand, H. 2015. Computer-Aided Dental Caries Detection System from X-Ray Images. In Computational Intelligence in Information Systems Springer. International Publishing. 233-243.
Rad, A. E., Rahim, M. S. M., & Norouzi, A. 2013. Digital Dental X-Ray Image Segmentation and Feature Extraction. TELKOMNIKA Indonesian Journal of Electrical Engineering. 11(6): 3109-3114.
Norouzi, A., Rahim, M. S. M., Altameem, A., Saba, T., Rad, A. E., Rehman, A., & Uddin, M. 2014. Medical Image Segmentation Methods, Algorithms, And Applications. IETE Technical Review. 31(3): 199-213.
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