Color MRI Image Segmentation Using Quantum-Inspired Modified Genetic Algorithm-Based FCM

  • Sunanda Das
  • Sourav De
  • Siddhartha Bhattacharyya
  • Aboul Ella Hassanien
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 727)

Abstract

A quantum counterpart of classical modified genetic algorithm-based FCM is presented in this article for color MRI image segmentation. Though classical modified GA enhances the global search optimality of conventional GA but to speed up and make it more optimal and cost effective, some quantum computing phenomena like qubit, superposition, entanglement, quantum gate are incorporated here. To achieve the final segmented output, the class levels generated by quantum-inspired modified genetic algorithm are now fed to conventional FCM to overcome the early convergence to local minima problem of FCM. A performance comparison is delineated between quantum-inspired modified GA-based FCM, quantum-inspired GA-based FCM and classical modified GA-based FCM based on two color MRI images.

Keywords

MRI image Image segmentation Modified genetic algorithm Quantum-inspired soft computing FCM 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Sunanda Das
    • 1
  • Sourav De
    • 2
  • Siddhartha Bhattacharyya
    • 3
  • Aboul Ella Hassanien
    • 4
  1. 1.Department of Computer Science and EngineeringUniversity Institute of TechnologyBurdwanIndia
  2. 2.Department of Computer Science and EngineeringCoochBehar Government Engineering CollegeCoochBeharIndia
  3. 3.Department of Computer ApplicationRCC Institute of Information TechnologyKolkataIndia
  4. 4.Information Technology DepartmentCairo UniversityCairoEgypt

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