Bio-inspired Optimization Algorithms for Segmentation and Removal of Interphase Cells from Metaphase Chromosomes Images

  • Gehad Ismail SayedEmail author
  • Aboul Ella Hassanien
Part of the Studies in Computational Intelligence book series (SCI, volume 801)


Interphase cells are undivided and the condensed mass of chromosomes. They can highly decrease the efficiency of automatic karyotype. karyotype is a test that is used to examine chromosomes. It includes counting the number of chromosomes and finding the structural changes in chromosomes. Manual karyotyping is a very challenging task and very time-consuming. This is due to the color similarity between interphase cells, chromosomes and parts of the background. In this chapter, two automatic approaches are proposed. The first approach is based on using Fast Fuzzy C-Means and Grey Wolf Optimization. The second approach is based on hybrid particle swarm optimization and K-Means algorithm. The proposed approaches are used to remove residual stains, interphase cells and to extract chromosomes from metaphase chromosomes image. The general architecture comprised of three fundamental phases: (1) Preprocessing, (2) Image segmentation based on either hybrid Particle Swarm Optimization and K-Means algorithm or Fast Fuzzy C-Means and Grey Wolf Optimization and (3) Post processing phase. 40 chromosomal images taken from albino rat bone marrow are used in this experiment. The experimental results showed the efficiency of the proposed segmentation and removal approaches. The proposed approach based on Fast Fuzzy C-Means and Grey Wolf Optimization obtained overall 94% accuracy. While, the proposed approach based on Particle Swarm Optimization and K-Means algorithm obtained overall 95% accuracy.


Chromosome image Genetic diseases Particle swarm optimization K-Means Interphase cells Grey Wolf optimization Fast fuzzy C-Means 


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Faculty of Computers and InformationCairo UniversityGizaEgypt
  2. 2.Scientific Research Group in Egypt (SRGE)GizaEgypt

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