1.
Kennedy, J., Eberhart, R.: Particle swarm optimization. In: IEEE International Conference on Neural Networks, Proceedings, pp. 1942–1948. IEEE, Perth (1995)
2.
Clerc, M.: Particle swarm optimization. ISTE Ltd (2006)
3.
Morel, J.-M., Solimini, S.: Variational methods in image segmentation: with seven image processing experiments, vol. 14. Springer, Boston (2012)
MATH
4.
McInerney, T., Terzopoulos, D.: Deformable models in medical image analysis: a survey. Med. Image Anal.
1, 91–108 (1996)
CrossRef
5.
Kass, M., Witkin, A., Terzopoulos, D.: Snakes: active contour models. Int. J. Comput. Vis.
1, 321–331 (1988)
CrossRefMATH
6.
Ballerini, L., Bocchi, L.: Multiple Genetic Snakes for Bone Segmentation. In: Raidl, G.R., Cagnoni, S., Cardalda, J.J., Corne, D.W., Gottlieb, J., Guillot, A., Hart, E., Johnson, C.G., Marchiori, E., Meyer, J.-A., Middendorf, M. (eds.) EvoIASP 2003, EvoWorkshops 2003, EvoSTIM 2003, EvoROB/EvoRobot 2003, EvoCOP 2003, EvoBIO 2003, and EvoMUSART 2003. LNCS, vol. 2611, pp. 346–356. Springer, Heidelberg (2003)
CrossRef
7.
Tsechpenakis, G., Rapantzikos, K., Tsapatsoulis, N., Kollias, S.: A snake model for object tracking in natural sequences.
19, 219–238 (2004)
8.
Niu, X.: A Geometric active contour model for highway extraction. In: Proceedings of ASPRS 2006 Annual Conference, Reno, Nevada (2006)
9.
Wildenauer, H., Blauensteiner, P., Hanbury, A., Kampel, M.: Motion detection using an improved colour model. In: Bebis, G., et al. (eds.) ISVC 2006. LNCS, vol. 4292, pp. 607–616. Springer, Heidelberg (2006)
CrossRef
10.
Karlsson, A., Stråhlén, K., Heyden, A.: A fast snake segmentation method applied to histopathological sections. In: Energy Minimization Methods in Computer Vision and Pattern Recognition. pp. 261–274. Springer Berlin Heidelberg (2003)
11.
Tseng, C., Hsieh, J., Jeng, J.: Active contour model via multi-population particle swarm optimization, (2009)
12.
Li, R., Guo, Y., Xing, Y., Li, M.: A Novel Multi-Swarm Particle Swarm Optimization algorithm Applied in Active Contour Model. In: Intelligent Systems, 2009. GCIS ’09. WRI Global Congress on. pp. 139–143. IEEE (2009)
13.
Ballerini, L.: Genetic snakes for medical images segmentation. In: Poli, R., Voigt, H.-M., Cagnoni, S., Corne, D.W., Smith, G.D., Fogarty, T.C. (eds.) EvoIASP 1999 and EuroEcTel 1999. LNCS, vol. 1596, pp. 59–73. Springer, Heidelberg (1999)
CrossRef
14.
Nebti, S., Meshoul, S.: Predator prey optimization for snake-based contour detection. Int. J. Intell. Comput. Cybern.
2, 228–242 (2009)
MathSciNetCrossRefMATH
15.
Zeng, D., Zhou, Z.: Invariant topology snakes driven by particle swarm optimizer. In: 2008 3rd International Conference on Innovative Computing Information and Control. p. 38. IEEE (2008)
16.
Shahamatnia, E., Ebadzadeh, M.M.: Application of particle swarm optimization and snake model hybrid on medical imaging. In: 2011 IEEE Third International Workshop on Computational Intelligence in Medical Imaging. pp. 1–8. IEEE, Paris, France (2011)
17.
Sharif, S.M., Qahwaji, R., Shahamatnia, E., Alzubaidi, R., Ipson, S., Brahma, A.: An efficient intelligent analysis system for confocal corneal endothelium images. Comput. Methods Programs Biomed.
122, 421–436 (2015)
CrossRef
18.
Shahamatnia, E., Dorotovič, I., Ribeiro, R.A., Fonseca, J.M.: Towards an automatic sunspot tracking: Swarm intelligence and snake model hybrid. Acta Futur.
5, 153–161 (2012)
19.
Shahamatnia, E., Dorotovič, I., Fonseca, J.M., Ribeiro, R.A.: An evolutionary computation based algorithm for calculating solar differential rotation by automatic tracking of coronal bright points. J. Sp. Weather Sp. Clim.
6, A16 (2016)
CrossRef
20.
Mora, A.D., Vieira, P.M., Manivannan, A., Fonseca, J.M.: Automated drusen detection in retinal images using analytical modelling algorithms. Biomed. Eng. Online.
10, 59 (2011)
CrossRef
21.
Brajša, R., Wöhl, H., Ruždjak, V., Clette, F., Hochedez, J.-F.: Solar differential rotation determined by tracing coronal bright points in SOHO-EIT images I. Interactive and automatic methods of data reduction. Astron. Astrophys.
374, 309–315 (2001)
CrossRef
22.
Gálvez, A., Iglesias, A.: A new iterative mutually coupled hybrid GA–PSO approach for curve fitting in manufacturing. Appl. Soft Comput.
13, 1491–1504 (2013)
CrossRef
23.
Shahamatnia, E., Dorotovi, I., Mora, A., Fonseca, J., Ribeiro, R.: Data inconsistency in sunspot detection. In: Filev, D., et al. (eds.) Intelligent Systems 2014, pp. 567–577. Springer, Cham (2015)
24.
Chen, B., LAI, J.H.: Active contour models on image segmentation: a survey. J. Image Graph. 1, (2007)
25.
Horng, M.-H., Liou, R.-J., Wu, J.: Parametric active contour model by using the honey bee mating optimization. Expert Syst. Appl.
37, 7015–7025 (2010)
CrossRef
26.
Van den Bergh, F.: An analysis of particle swarm optimizers, (2002)
27.
Shahamatnia, E., Dorotovic, I., Fonseca, J., Ribeiro, R.: On the importance of an automated and modular solar image processing tool. In: Proceedings of the European Planetary Science Congress (EPSC), Portugal (2014)
28.
Hakkinen, A., Muthukrishnan, A.-B., Mora, A., Fonseca, J.M., Ribeiro, A.S.: Cell Aging: a tool to study segregation and partitioning in division in cell lineages of Escherichia coli. Bioinformatics
29, 1708–1709 (2013)
CrossRef
29.
Häkkinen, A., Muthukrishnan, A.B., Mora, A., Fonseca, J.M., Ribeiro, A.S.: Cell Aging: a tool to study segregation and partitioning in division in cell lineages of Escherichia coli. Bioinformatics
29, 1708–1709 (2013)
CrossRef
30.
Lorenc, M., Rybanský, M., Dorotovič, I.: On rotation of the solar corona. Sol. Phys.
281, 611–619 (2012)
CrossRef
31.
Hara, H.: Differential rotation rate of X-ray bright points and source region of their magnetic fields. Astrophys. J.
697, 980 (2009)
CrossRef
32.
Brajša, R., Wöhl, H., Vršnak, B., Ruždjak, V., Clette, F., Hochedez, J.-F., Roša, D.: Height correction in the measurement of solar differential rotation determined by coronal bright points. Astron. Astrophys.
414, 707–715 (2004)
CrossRef
