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Research Article

Modified genetic algorithm for optimal classification of abnormal MRI tissues using hybrid model with discriminative learning approach

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Pages 14-21 | Received 14 Mar 2021, Accepted 08 Jul 2021, Published online: 26 Jul 2021

References

  • Abdel-Khalek S, Ishak AB, Omer OA, Obadaa ASF. 2017. A two-dimensional image segmentation method based on genetic algorithm and entropy. Opt J Light Electron Opt. 131(10):414–422. doi:10.1016/j.ijleo.2016.11.039.
  • Aswathy SU, Glan Devadhas G, Kumar SS. 2020. A tumour segmentation approach from FLAIR MRI brain images using SVM and genetic algorithm. Int J Biomed Eng Technol. 33(4):386–397. doi:10.1504/IJBET.2020.108993.
  • Ayachi R, Ben Amor N. 2009. Brain tumor segmentation using support vector machines. In: Sossai C, Chemello G, editors. Symb quant approaches to reason with uncertainty ECSQARU 2009 Lect Notes Comput Sci. Vol. 5590, (pp. 736–747). Springer, Berlin, Heidelberg; [accessed 2021 Jun 6]. https://link.springer.com/chapter/10.1007/978-3-642-02906-6_63
  • Bahadure NB, Ray AK, Thethi HP. 2017. Image analysis for MRI based brain tumor detection and feature extraction using biologically inspired BWT and SVM. Int J Biomed Imaging. 2017:1–12. doi:10.1155/2017/9749108.
  • Belgrana FZ, Benamrane N, Kasmi SA. 2020. A hybrid segmentation approach of brain magnetic resonance imaging using region-based active contour with a similarity factor and multi-population genetic algorithm. Pattern Recognit Image Anal. 30(4):765–777. doi:10.1134/S1054661820040069.
  • De S, Bhattacharyya S, Dutta P. 2016. Automatic magnetic resonance image segmentation by fuzzy intercluster hostility index based genetic algorithm: an application. Appl Soft Comput J. 47:669–683. doi:10.1016/j.asoc.2016.05.042.
  • Dubey YK, Mushrif MM. 2016. FCM clustering algorithms for segmentation of brain MR images. Adv Fuzzy Syst. 2016:14.
  • El Zahab Z, Divo E, Kassab A. 2010. Minimisation of the wall shear stress gradients in bypass grafts anastomoses using meshless CFD and genetic algorithms optimisation. Comput Methods Biomech Biomed Engin. 13(1):35–47. doi:10.1080/10255840903013555.
  • Ghosh P, Mitchell M, Tanyi JA, Hung AY. 2016. Incorporating priors for medical image segmentation using a genetic algorithm. Neurocomputing. 195:181–194. doi:10.1016/j.neucom.2015.09.123.
  • Haralick RM, Shanmugam K, Dinstein I. 1973. Textural features for image classification. IEEE Trans Syst Man Cybern. SMC-3(6):610–621. doi:10.1109/tsmc.1973.4309314.
  • Havaei M, Davy A, Warde-Farley D, Biard A, Courville A, Bengio Y, Pal C, Jodoin PM, Larochelle H. 2017. Brain tumor segmentation with deep neural networks. Med Image Anal. 35:18–31. doi:10.1016/j.media.2016.05.004.
  • Hemanth DJ, Anitha J. 2019. Modified genetic algorithm approaches for classification of abnormal magnetic resonance brain tumour images. Appl Soft Comput J. 75:21–28. doi:10.1016/j.asoc.2018.10.054.
  • Hernández-Gascón B, Espés N, Peña E, Pascual G, Bellón JM, Calvo B. 2014. Computational framework to model and design surgical meshes for hernia repair. Comput Methods Biomech Biomed Engin. 17(10):1071–1085. doi:10.1080/10255842.2012.736967.
  • Huang Z, Xu H, Su S, Wang T, Luo Y, Zhao X, Liu Y, Song G, Zhao Y. 2020. A computer-aided diagnosis system for brain magnetic resonance imaging images using a novel differential feature neural network. Comput Biol Med. 121:103818. doi:10.1016/j.compbiomed.2020.103818.
  • Javadpour A, Mohammadi A. 2016. Improving brain magnetic resonance image segmentation via a novel algorithm based on genetic and regional growth. J Biomed Phys Eng. 6(2):95–108.
  • Joans DSM, Sandhiya J. 2017. A genetic algorithm based feature selection for classification of brain MRI scan images using random forest classifier. Int J Adv Eng Res Sci. 4(5):131–136. doi:10.22161/ijaers.4.5.21.
  • Kavitha AR, Chellamuthu C. 2016. Brain tumour segmentation from MRI image using genetic algorithm with fuzzy initialisation and seeded modified region growing (GFSMRG) method. Imaging Sci J. 64(5):285–297. doi:10.1080/13682199.2016.1178412.
  • Krzeszowski T, Przednowek K, Wiktorowicz K, Iskra J. 2016. Estimation of hurdle clearance parameters using a monocular human motion tracking method. Comput Methods Biomech Biomed Engin. 19(12):1319–1329. doi:10.1080/10255842.2016.1139092.
  • Lai CC, Chang CY. 2009. A hierarchical evolutionary algorithm for automatic medical image segmentation. Expert Syst Appl. 36(1):248–259. doi:10.1016/j.eswa.2007.09.003.
  • Manikandan S, Ramar K, Iruthayarajan MW, Srinivasagan KG. 2014. Multilevel thresholding for segmentation of medical brain images using real coded genetic algorithm. Measurement. 47:558–568. doi:10.1016/j.measurement.2013.09.031.
  • Materka A, Strzelecki M. 1998. Texture analysis methods - a review. COST B11 report, Brussels 1998; [accessed 2021 Mar 14]. http://citeseer.ist.psu.edu/viewdoc/summary?doi=10.1.1.97.4968
  • Maulik U. 2009. Medical image segmentation using genetic algorithms. IEEE Trans Inf Technol Biomed. 13(2):166–173. doi:10.1109/TITB.2008.2007301.
  • Mehrian M, Geris L. 2020. Optimizing neotissue growth inside perfusion bioreactors with respect to culture and labor cost: a multi-objective optimization study using evolutionary algorithms. Comput Methods Biomech Biomed Engin. 23(7):285–294. doi:10.1080/10255842.2020.1719081.
  • Menze BH, Jakab A, Bauer S, Kalpathy-Cramer J, Farahani K, Kirby J, Burren Y, Porz N, Slotboom J, Wiest R, et al. 2015. The multimodal brain tumor image segmentation benchmark (BRATS). IEEE Trans Med Imaging. 34(10):1993–2024. doi:10.1109/TMI.2014.2377694.
  • Motieghader H, Najafi A, Sadeghi B, Masoudi-Nejad A. 2017. A hybrid gene selection algorithm for microarray cancer classification using genetic algorithm and learning automata. Inform Med Unlocked. 9:(August):246–254. doi:10.1016/j.imu.2017.10.004.
  • Nagarajan G, Minu RI, Muthukumar B, Vedanarayanan V, Sundarsingh SD. 2016. Hybrid genetic algorithm for medical image feature extraction and selection. Procedia Comput Sci. 85:455–462. doi:10.1016/j.procs.2016.05.192.
  • Nematzadeh H, Enayatifar R, Motameni H, Guimarães FG, Coelho VN. 2018. Medical image encryption using a hybrid model of modified genetic algorithm and coupled map lattices. Opt Lasers Eng. 110(May):24–32. doi:10.1016/j.optlaseng.2018.05.009.
  • Oliveira GC, Varoto R, Cliquet A 2018. Brain tumor segmentation in magnetic resonance images using genetic algorithm clustering and adaboost classifier. BIOIMAGING 2018-5th Int Conf Bioimaging, Proceedings; Part 11th Int Jt Conf Biomed Eng Syst Technol BIOSTEC 2018. SCITEPRESS – Science and Technology Publications, Lda, Funchal, Madeira, Portugal, 2018; p. 77–82.
  • Rundo L, Militello C, Tangherloni A, Russo G, Vitabile S, Gilardi MC, Mauri G. 2018. NeXt for neuro-radiosurgery: a fully automatic approach for necrosis extraction in brain tumor MRI using an unsupervised machine learning technique. Int J Imaging Syst Technol. 28(1):21–37. doi:10.1002/ima.22253.
  • Rundo L, Tangherloni A, Cazzaniga P, Nobile MS, Russo G, Gilardi MC, Vitabile S, Mauri G, Besozzi D, Militello C. 2019b. A novel framework for MR image segmentation and quantification by using MedGA. Comput Methods Programs Biomed. 176:159–172. doi:10.1016/j.cmpb.2019.04.016.
  • Rundo L, Tangherloni A, Nobile MS, Militello C, Besozzi D, Mauri G, Cazzaniga P. 2019a. MedGA: a novel evolutionary method for image enhancement in medical imaging systems. Expert Syst Appl. 119:387–399. doi:10.1016/j.eswa.2018.11.013.
  • Sharif MI, Khan MA, Alhussein M, Aurangzeb K, Raza M. 2021. A decision support system for multimodal brain tumor classification using deep learning. Complex Intell Syst. 1:3. doi:10.1007/s40747-021-00321-0.
  • Sharma M, Singh G, Singh R. 2018. Clinical decision support system query optimizer using hybrid Firefly and controlled Genetic Algorithm. J King Saud Univ Comput Inf Sci. 32(10):1206–1207.
  • Wang C, Wang L, Liu X, Fan Y. 2014. Numerical simulation of the remodelling process of trabecular architecture around dental implants. Comput Methods Biomech Biomed Engin. 17(3):286–295. doi:10.1080/10255842.2012.681646.
  • Wang S-H, Zhou Q, Yang M, Zhang Y-D. 2021. ADVIAN: alzheimer’s disease VGG-inspired attention network based on convolutional block attention module and multiple way data augmentation. Front Aging Neurosci. 13(687456):1–15. doi:10.3389/fnagi.2021.687456.
  • Yeh JY, Fu JC. 2008. A hierarchical genetic algorithm for segmentation of multi-spectral human-brain MRI. Expert Syst Appl. 34(2):1285–1295. doi:10.1016/j.eswa.2006.12.012.
  • Zhang YD, Dong Z, Wang SH, Yu X, Yao X, Zhou Q, Hu H, Li M, Jiménez-Mesa C, Ramirez J, et al. 2020. Advances in multimodal data fusion in neuroimaging: overview, challenges, and novel orientation. Inf Fusion. 64:149–187.

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