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2017 | OriginalPaper | Chapter

4. Particle Swarm Optimization Based Fast Chan-Vese Algorithm for Medical Image Segmentation

Authors : Devraj Mandal, Amitava Chatterjee, Madhubanti Maitra

Published in: Metaheuristics for Medicine and Biology

Publisher: Springer Berlin Heidelberg

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Abstract

Image segmentation is a very important part of image pre-processing and its application towards computer vision.

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Literature
2.
go back to reference E.S. Brown, T. Chan, X. Bresson, Completely convex formulation of the Chan-Vese image segmentation model. Int. J. Comput. Vis. 98, 103–121 (2012)MathSciNetCrossRefMATH E.S. Brown, T. Chan, X. Bresson, Completely convex formulation of the Chan-Vese image segmentation model. Int. J. Comput. Vis. 98, 103–121 (2012)MathSciNetCrossRefMATH
3.
4.
go back to reference V. Caselles, R. Kimmel, G. Sapiro, On geodesic active contours. Int. J. Comput. Vis. 22(1), 61–79 (1997)CrossRefMATH V. Caselles, R. Kimmel, G. Sapiro, On geodesic active contours. Int. J. Comput. Vis. 22(1), 61–79 (1997)CrossRefMATH
5.
go back to reference T. Chan, B.Y. Sandberg, L. Vese, Active contours without edges for Vector-Valued images. J. Vis. Commun. Image Represent. 11, 130–141 (1999)CrossRef T. Chan, B.Y. Sandberg, L. Vese, Active contours without edges for Vector-Valued images. J. Vis. Commun. Image Represent. 11, 130–141 (1999)CrossRef
6.
go back to reference T. Chan, L. Vese, Active contours without edges. IEEE Trans. Image Process. 10(2), 266–277 (2001)CrossRefMATH T. Chan, L. Vese, Active contours without edges. IEEE Trans. Image Process. 10(2), 266–277 (2001)CrossRefMATH
7.
go back to reference A. Chander, A. Chatterjee, P. Siarry, A new social and momentum component adaptive PSO algorithm for image segmentation. Expert Syst. Appl. 38(5), 4998–5004 (2011)CrossRef A. Chander, A. Chatterjee, P. Siarry, A new social and momentum component adaptive PSO algorithm for image segmentation. Expert Syst. Appl. 38(5), 4998–5004 (2011)CrossRef
8.
go back to reference A. Chatterjee, F. Matsuno, A neuro-fuzzy assisted extended Kalman filter-based approach for Simultaneous Localization and Mapping (SLAM) problems. IEEE Trans. Fuzzy Syst. 15(5), 984–997 (2007)CrossRef A. Chatterjee, F. Matsuno, A neuro-fuzzy assisted extended Kalman filter-based approach for Simultaneous Localization and Mapping (SLAM) problems. IEEE Trans. Fuzzy Syst. 15(5), 984–997 (2007)CrossRef
9.
go back to reference A. Chatterjee, F. Matsuno, A geese PSO tuned fuzzy supervisor for EKF based solutions of simultaneous localization and mapping (SLAM) problems in mobile robots. Expert Syst. Appl. 37(8), 5542–5548 (2010)CrossRef A. Chatterjee, F. Matsuno, A geese PSO tuned fuzzy supervisor for EKF based solutions of simultaneous localization and mapping (SLAM) problems in mobile robots. Expert Syst. Appl. 37(8), 5542–5548 (2010)CrossRef
10.
go back to reference A. Chatterjee, P. Siarry (eds.), Computational Intelligence in Image Processing (Springer, Heidelberg, 2013) A. Chatterjee, P. Siarry (eds.), Computational Intelligence in Image Processing (Springer, Heidelberg, 2013)
11.
go back to reference A. Chatterjee, K. Pulasinghe, K. Watanabe, K. Izumi, A particle swarm optimized fuzzy-neural network for voice-controlled robot systems. IEEE Trans. Ind. Electron. 52(6), 1478–1489 (2005)CrossRef A. Chatterjee, K. Pulasinghe, K. Watanabe, K. Izumi, A particle swarm optimized fuzzy-neural network for voice-controlled robot systems. IEEE Trans. Ind. Electron. 52(6), 1478–1489 (2005)CrossRef
12.
go back to reference A. Chatterjee, R. Chatterjee, F. Matsuno, T. Endo, Neuro-fuzzy state modeling of flexible robotic arm employing dynamically varying cognitive and social component based PSO. Measurement 40(6), 628–643 (2007)CrossRef A. Chatterjee, R. Chatterjee, F. Matsuno, T. Endo, Neuro-fuzzy state modeling of flexible robotic arm employing dynamically varying cognitive and social component based PSO. Measurement 40(6), 628–643 (2007)CrossRef
13.
go back to reference A. Chatterjee, M. Dutta, A. Rakshit, An intelligent method of impedance measurement employing PSO-aided neuro fuzzy system with LMS algorithm, in Proceedings of the IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2007), London, UK, 23–26 July 2007 A. Chatterjee, M. Dutta, A. Rakshit, An intelligent method of impedance measurement employing PSO-aided neuro fuzzy system with LMS algorithm, in Proceedings of the IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2007), London, UK, 23–26 July 2007
14.
go back to reference A. Chatterjee, R. Chatterjee, F. Matsuno, T. Endo, Augmented stable fuzzy control for flexible robotic arm using LMI approach and neuro-fuzzy state space modeling. IEEE Trans. Ind. Electron. 55(3), 1256–1270 (2008)CrossRef A. Chatterjee, R. Chatterjee, F. Matsuno, T. Endo, Augmented stable fuzzy control for flexible robotic arm using LMI approach and neuro-fuzzy state space modeling. IEEE Trans. Ind. Electron. 55(3), 1256–1270 (2008)CrossRef
15.
go back to reference A. Chatterjee, P. Siarry, A. Nakib, R. Blanc, An improved biogeography based optimization approach for segmentation of human head ct-scan images employing fuzzy entropy. Eng. Appl. Artif. Intell. 25, 1698–1709 (2012)CrossRef A. Chatterjee, P. Siarry, A. Nakib, R. Blanc, An improved biogeography based optimization approach for segmentation of human head ct-scan images employing fuzzy entropy. Eng. Appl. Artif. Intell. 25, 1698–1709 (2012)CrossRef
16.
go back to reference A. Chatterjee, H. Nobahari, P. Siarry (eds.), Advances in Heuristic Signal Processing and Applications (Springer, Heidelberg, 2013)MATH A. Chatterjee, H. Nobahari, P. Siarry (eds.), Advances in Heuristic Signal Processing and Applications (Springer, Heidelberg, 2013)MATH
18.
go back to reference M. Clerc, J. Kennedy, The particle swarm: explosion, stability, and convergence in a multi-dimensional complex space, in IEEE Transactions on Evolutionary Computation, Piscataway, NJ, (2002), p. 5873 M. Clerc, J. Kennedy, The particle swarm: explosion, stability, and convergence in a multi-dimensional complex space, in IEEE Transactions on Evolutionary Computation, Piscataway, NJ, (2002), p. 5873
19.
go back to reference K. Das Sharma, A. Chatterjee, A. Rakshit, A PSO-Lyapunov hybrid stable adaptive fuzzy tracking control approach for vision based robot navigation. IEEE Trans. Instrum. Measurement 61(7), 908–1914 (2012)CrossRef K. Das Sharma, A. Chatterjee, A. Rakshit, A PSO-Lyapunov hybrid stable adaptive fuzzy tracking control approach for vision based robot navigation. IEEE Trans. Instrum. Measurement 61(7), 908–1914 (2012)CrossRef
20.
go back to reference K. Das Sharma, A. Chatterjee, A. Rakshit, A random spatial lbest PSO-based hybrid strategy for designing adaptive fuzzy controllers for a class of nonlinear systems. IEEE Trans. Instrum. Meas. 61(6), 1605–1612 (2012)CrossRef K. Das Sharma, A. Chatterjee, A. Rakshit, A random spatial lbest PSO-based hybrid strategy for designing adaptive fuzzy controllers for a class of nonlinear systems. IEEE Trans. Instrum. Meas. 61(6), 1605–1612 (2012)CrossRef
21.
go back to reference R.L. Dice, Measures of the amount of ecologic association between species. Ecology 26, 297–302 (1945)CrossRef R.L. Dice, Measures of the amount of ecologic association between species. Ecology 26, 297–302 (1945)CrossRef
33.
go back to reference J.H. Holland, Adaptation in Natural and Artificial Systems (MIT Press, Cambridge, 1992) J.H. Holland, Adaptation in Natural and Artificial Systems (MIT Press, Cambridge, 1992)
34.
go back to reference M. Jamalipour et al., Quantum behaved particle swarm optimization with differential mutation operator applied to WWER-1000 in-core fuel management optimization. Ann. Nucl. Energy 54, 134–140 (2013)CrossRef M. Jamalipour et al., Quantum behaved particle swarm optimization with differential mutation operator applied to WWER-1000 in-core fuel management optimization. Ann. Nucl. Energy 54, 134–140 (2013)CrossRef
35.
go back to reference M. Kass, A. Witkin, D. Terzopoulos, Snakes: active contour models. Int. J. Comput. Vis. 1, 321–331 (1988)CrossRefMATH M. Kass, A. Witkin, D. Terzopoulos, Snakes: active contour models. Int. J. Comput. Vis. 1, 321–331 (1988)CrossRefMATH
36.
go back to reference J. Kennedy, R. Eberhart, Particle swarm optimization. Proc. IEEE Int. Jt. Conf. Neural Netw. Perth Aust. 4, 1942–1948 (1995) J. Kennedy, R. Eberhart, Particle swarm optimization. Proc. IEEE Int. Jt. Conf. Neural Netw. Perth Aust. 4, 1942–1948 (1995)
37.
go back to reference S. Kichenassamy, A. Kumar, P. Olver, A. Tannenbaum, A. Yezzy, Gradient flows and geometric active contour models, in Proceedings of the International Conference on Computer Vision, Cambridge, MA, (1995), p. 810815 S. Kichenassamy, A. Kumar, P. Olver, A. Tannenbaum, A. Yezzy, Gradient flows and geometric active contour models, in Proceedings of the International Conference on Computer Vision, Cambridge, MA, (1995), p. 810815
38.
go back to reference M.-S. Lee, G. Medioni, Inferred descriptions in terms of curves, regions and junctions from sparse, noisy binary data, in Proceedings of the IEEE International Symposium on Computer Vision, Coral Gables, FL, (1995), p. 7378 M.-S. Lee, G. Medioni, Inferred descriptions in terms of curves, regions and junctions from sparse, noisy binary data, in Proceedings of the IEEE International Symposium on Computer Vision, Coral Gables, FL, (1995), p. 7378
39.
go back to reference C. Li, C. Xu, C. Gui, M.D. Fox, Level set evolution without re-initialization: a new variational formulation, in Proceedings of the IEEE Conference Computer Vision and Pattern Recognition, vol. 1, (2005), pp. 430–436 C. Li, C. Xu, C. Gui, M.D. Fox, Level set evolution without re-initialization: a new variational formulation, in Proceedings of the IEEE Conference Computer Vision and Pattern Recognition, vol. 1, (2005), pp. 430–436
40.
go back to reference S. Li, Q. Zhang, Fast Image Segmentation Based on Efficient Implementation of the Chan-Vese Model with Discrete Gray Level Sets, on Mathematical Problems in Engineering (2013) S. Li, Q. Zhang, Fast Image Segmentation Based on Efficient Implementation of the Chan-Vese Model with Discrete Gray Level Sets, on Mathematical Problems in Engineering (2013)
41.
go back to reference Y. Liu, K.M. Passino, Biomimicry of social foraging Bacteria for distributed optimization: models, principles, and emergent behaviors. J. Optim. Theory Appl. 115, 603–628 (2002)MathSciNetCrossRefMATH Y. Liu, K.M. Passino, Biomimicry of social foraging Bacteria for distributed optimization: models, principles, and emergent behaviors. J. Optim. Theory Appl. 115, 603–628 (2002)MathSciNetCrossRefMATH
42.
go back to reference F. Liu, H. Duan, Y. Deng, A chaotic quantum-behaved particle swarm optimization based on lateral inhibition for image matching. Optik - Int. J. Light Electron Optics 123, 1955–1960 (2012)CrossRef F. Liu, H. Duan, Y. Deng, A chaotic quantum-behaved particle swarm optimization based on lateral inhibition for image matching. Optik - Int. J. Light Electron Optics 123, 1955–1960 (2012)CrossRef
44.
go back to reference M. Maitra, A. Chatterjee, A hybrid cooperative comprehensive learning based PSO algorithm for image segmentation using multilevel thresholding. Expert Syst. Appl. 34(2), 1341–1350 (2008)CrossRef M. Maitra, A. Chatterjee, A hybrid cooperative comprehensive learning based PSO algorithm for image segmentation using multilevel thresholding. Expert Syst. Appl. 34(2), 1341–1350 (2008)CrossRef
45.
go back to reference M. Maitra, A. Chatterjee, A novel technique for multilevel optimal magnetic resonance brain image thresholding using bacterial foraging. Measurement 41(10), 1124–1134 (2008)CrossRef M. Maitra, A. Chatterjee, A novel technique for multilevel optimal magnetic resonance brain image thresholding using bacterial foraging. Measurement 41(10), 1124–1134 (2008)CrossRef
46.
go back to reference R. Malladi, J.A. Sethian, B.C. Vemuri, A topology independent shape modelling scheme, in Proceedings of the Trento Conference Geometric Methods Computer Vision II, San Diego, CA, vol. 2031, (1993), pp. 246–258 R. Malladi, J.A. Sethian, B.C. Vemuri, A topology independent shape modelling scheme, in Proceedings of the Trento Conference Geometric Methods Computer Vision II, San Diego, CA, vol. 2031, (1993), pp. 246–258
47.
go back to reference R. Malladi, J.A. Sethian, B.C. Vemuri, Shape modeling with front propagation: a level set approach. IEEE Trans. Pattern Anal. Mach. Intell. 17, 158–175 (1995)CrossRef R. Malladi, J.A. Sethian, B.C. Vemuri, Shape modeling with front propagation: a level set approach. IEEE Trans. Pattern Anal. Mach. Intell. 17, 158–175 (1995)CrossRef
49.
go back to reference D. Mumford, J. Shah, Optimal approximation by piecewise smooth functions and associated variational problems. Commun. Pure Appl. Math. 42, 577–685 (1989)MathSciNetCrossRefMATH D. Mumford, J. Shah, Optimal approximation by piecewise smooth functions and associated variational problems. Commun. Pure Appl. Math. 42, 577–685 (1989)MathSciNetCrossRefMATH
50.
go back to reference S. Osher, J.A. Sethian, Fronts propagating with curvature-dependent speed: algorithms based on Hamilton–Jacobi formulation. J. Comput. Phys. 79, 12–49 (1988)MathSciNetCrossRefMATH S. Osher, J.A. Sethian, Fronts propagating with curvature-dependent speed: algorithms based on Hamilton–Jacobi formulation. J. Comput. Phys. 79, 12–49 (1988)MathSciNetCrossRefMATH
52.
go back to reference N. Sanyal, A. Chatterjee, S. Munshi, An adaptive bacterial foraging algorithm for fuzzy entropy based image segmentation. Expert Syst. Appl. 38(12), 15489–15498 (2011)CrossRef N. Sanyal, A. Chatterjee, S. Munshi, An adaptive bacterial foraging algorithm for fuzzy entropy based image segmentation. Expert Syst. Appl. 38(12), 15489–15498 (2011)CrossRef
53.
go back to reference K. Sharma, A. Chatterjee, A. Rakshit, A hybrid approach for design of stable adaptive fuzzy controllers employing Lyapunov theory and particle swarm optimization. IEEE Trans. Fuzzy Syst. 17(2), 329–342 (2009)CrossRef K. Sharma, A. Chatterjee, A. Rakshit, A hybrid approach for design of stable adaptive fuzzy controllers employing Lyapunov theory and particle swarm optimization. IEEE Trans. Fuzzy Syst. 17(2), 329–342 (2009)CrossRef
54.
go back to reference Y. Shi, R. Eberhart, A modified particle swarm optimizer, in Proceedings of the IEEE International Conference on Evolutionary Computation, pp. 69–73 Y. Shi, R. Eberhart, A modified particle swarm optimizer, in Proceedings of the IEEE International Conference on Evolutionary Computation, pp. 69–73
55.
go back to reference J.E. Solem, N.C. Overgaard, A. Heyden, Initialization techniques for segmentation with the Chan Vese model. Proc. Int. Conf. Pattern Recognit. 2, 171–174 (2006) J.E. Solem, N.C. Overgaard, A. Heyden, Initialization techniques for segmentation with the Chan Vese model. Proc. Int. Conf. Pattern Recognit. 2, 171–174 (2006)
56.
go back to reference T. Sorensen, A method of establishing groups of equal amplitude in plant sociology based on similarity of species and its application to analyses of the vegetation on Danish commons, Kongelige Danske Videnskabernes Selskab, vol. 5, (1957), pp. 1–34 T. Sorensen, A method of establishing groups of equal amplitude in plant sociology based on similarity of species and its application to analyses of the vegetation on Danish commons, Kongelige Danske Videnskabernes Selskab, vol. 5, (1957), pp. 1–34
57.
go back to reference J. Sun, B. Feng, W. Xu, Particle swarm optimization with particles having quantum behavior. IEEE Proc. Congr. Evol. Comput. 1, 325331 (2004) J. Sun, B. Feng, W. Xu, Particle swarm optimization with particles having quantum behavior. IEEE Proc. Congr. Evol. Comput. 1, 325331 (2004)
58.
go back to reference J. Sun, B. Feng, W. Xu, Adaptive parameter control for quantum behaved particle swarm optimization on individual level, in Proceedings of the 2005 IEEE International Conference on Systems, Man, and Cybernetics, vol. 4, (2005), pp. 30493054 J. Sun, B. Feng, W. Xu, Adaptive parameter control for quantum behaved particle swarm optimization on individual level, in Proceedings of the 2005 IEEE International Conference on Systems, Man, and Cybernetics, vol. 4, (2005), pp. 30493054
59.
go back to reference M. Sussman, P. Smereka, S. Osher, A level set approach for computing solutions to incompressible two-phase flow. J. Comput. Phys. 119, 146159 (1994)MATH M. Sussman, P. Smereka, S. Osher, A level set approach for computing solutions to incompressible two-phase flow. J. Comput. Phys. 119, 146159 (1994)MATH
60.
go back to reference L. Vese, T. Chan, A multiphase level set framework for image segmentation using the Mumford and Shah model. Int. J. Comput. Vis. 50, 271–293 (2002)CrossRefMATH L. Vese, T. Chan, A multiphase level set framework for image segmentation using the Mumford and Shah model. Int. J. Comput. Vis. 50, 271–293 (2002)CrossRefMATH
61.
go back to reference C. Xu, J.L. Prince, Snakes, shapes and gradient vector flow. IEEE Trans. Image Proces. 7, 359369 (1998)MathSciNetMATH C. Xu, J.L. Prince, Snakes, shapes and gradient vector flow. IEEE Trans. Image Proces. 7, 359369 (1998)MathSciNetMATH
62.
go back to reference T.A. Yezzi, A.S. Willsky, Curve evolution implementation of the Mumford-Shah functional for image segmentation, denoising, interpolation, and magnification. IEEE Trans. Image Process. 10(8), 1169–1186 (2001)CrossRefMATH T.A. Yezzi, A.S. Willsky, Curve evolution implementation of the Mumford-Shah functional for image segmentation, denoising, interpolation, and magnification. IEEE Trans. Image Process. 10(8), 1169–1186 (2001)CrossRefMATH
63.
go back to reference H.K. Zhao, T. Chan, B. Merriman, S. Osher, A variational level set approach to multiphase motion. J. Comput. Phys. 127, 179195 (1996)MathSciNetCrossRefMATH H.K. Zhao, T. Chan, B. Merriman, S. Osher, A variational level set approach to multiphase motion. J. Comput. Phys. 127, 179195 (1996)MathSciNetCrossRefMATH
64.
go back to reference S.C. Zhu, T.S. Lee, A.L. Yuille, Region competition: unifying snakes, region growing, energy/bayes/MDL for multi-band image segmentation, in Proceedings of the IEEE 5th International Conference on Computer Vision, Cambridge, MA, (1995), p. 416423 S.C. Zhu, T.S. Lee, A.L. Yuille, Region competition: unifying snakes, region growing, energy/bayes/MDL for multi-band image segmentation, in Proceedings of the IEEE 5th International Conference on Computer Vision, Cambridge, MA, (1995), p. 416423
Metadata
Title
Particle Swarm Optimization Based Fast Chan-Vese Algorithm for Medical Image Segmentation
Authors
Devraj Mandal
Amitava Chatterjee
Madhubanti Maitra
Copyright Year
2017
Publisher
Springer Berlin Heidelberg
DOI
https://doi.org/10.1007/978-3-662-54428-0_4

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