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Article Dans Une Revue Journal of Bionic Engineering Année : 2023

Improved Reptile Search Algorithm by Salp Swarm Algorithm for Medical Image Segmentation

Laith Abualigah
Mahmoud Habash
  • Fonction : Auteur
Essam Said Hanandeh
  • Fonction : Auteur
Ahmad Mohdaziz Hussein
  • Fonction : Auteur
Mohammad Al Shinwan
  • Fonction : Auteur
Heming Jia
  • Fonction : Auteur

Résumé

This study proposes a novel nature-inspired meta-heuristic optimizer based on the Reptile Search Algorithm combed with Salp Swarm Algorithm for image segmentation using gray-scale multi-level thresholding, called RSA-SSA. The proposed method introduces a better search space to find the optimal solution at each iteration. However, we proposed RSA-SSA to avoid the searching problem in the same area and determine the optimal multi-level thresholds. The obtained solutions by the proposed method are represented using the image histogram. The proposed RSA-SSA employed Otsu’s variance class function to get the best threshold values at each level. The performance measure for the proposed method is valid by detecting fitness function, structural similarity index, peak signal-to-noise ratio, and Friedman ranking test. Several benchmark images of COVID-19 validate the performance of the proposed RSA-SSA. The results showed that the proposed RSA-SSA outperformed other metaheuristics optimization algorithms published in the literature.
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Dates et versions

hal-03978077 , version 1 (08-02-2023)

Identifiants

Citer

Laith Abualigah, Mahmoud Habash, Essam Said Hanandeh, Ahmad Mohdaziz Hussein, Mohammad Al Shinwan, et al.. Improved Reptile Search Algorithm by Salp Swarm Algorithm for Medical Image Segmentation. Journal of Bionic Engineering, 2023, ⟨10.1007/s42235-023-00332-2⟩. ⟨hal-03978077⟩

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