An enhanced spider wasp optimization algorithm for multilevel thresholding-based medical image segmentation DOI

Mohamed Abdel-Basset,

Reda Mohamed, Ibrahim M. Hezam

et al.

Evolving Systems, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 1, 2024

Language: Английский

A gazelle optimization expedition for key term separated fractional nonlinear systems with application to electrically stimulated muscle modeling DOI
Taimoor Ali Khan, Naveed Ishtiaq Chaudhary, Chung-Chian Hsu

et al.

Chaos Solitons & Fractals, Journal Year: 2024, Volume and Issue: 185, P. 115111 - 115111

Published: June 15, 2024

Language: Английский

Citations

7
Optimizing cancer diagnosis: A hybrid approach of genetic operators and Sinh Cosh Optimizer for tumor identification and feature gene selection DOI

Marwa M. Emam,

Essam H. Houssein, Nagwan Abdel Samee

et al.

Computers in Biology and Medicine, Journal Year: 2024, Volume and Issue: 180, P. 108984 - 108984

Published: Aug. 10, 2024

Language: Английский

Citations

6
An enhanced exponential distribution optimizer and its application for multi-level medical image thresholding problems DOI Creative Commons
Fatma A. Hashim, Abdelazim G. Hussien, Anas Bouaouda

et al.

Alexandria Engineering Journal, Journal Year: 2024, Volume and Issue: 93, P. 142 - 188

Published: March 15, 2024

In this paper, an enhanced version of the Exponential Distribution Optimizer (EDO) called mEDO is introduced to tackle global optimization and multi-level image segmentation problems. EDO a math-inspired optimizer that has many limitations in handling complex multi-modal tries solve these drawbacks using 2 operators: phasor operator for diversity enhancement adaptive p-best mutation strategy preventing it converging local optima. To validate effectiveness suggested optimizer, comprehensive set comparative experiments CEC'2020 test suite was conducted. The experimental results consistently prove technique outperforms its counterparts terms both convergence speed accuracy. Moreover, algorithm applied multi-threshold method with Otsu's entropy, providing further evidence performance. evaluated by comparing those existing well-known algorithms at various threshold levels. proposed attains exceptional

Language: Английский

Citations

5
Polyp image segmentation based on improved planet optimization algorithm using reptile search algorithm DOI Creative Commons
Mohamed Abd Elaziz, Mohammed A. A. Al‐qaness, Mohammed Azmi Al‐Betar

et al.

Neural Computing and Applications, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 12, 2025

Abstract To recognize the potential for colon polyps to develop into cancer over time, early diagnosis is crucial preventative healthcare. Timely identification significantly improves prognosis and treatment outcomes colorectal patients. Image segmentation in medical image analysis accurate planning. Therefore, this study, we present an alternative multilevel thresholding polyp method (MPOA) enhance of images. The proposed based on enhancing planet optimization algorithm (POA) by integrating operators from reptile search (RSA). evaluation developed MPOA tested with different images compared other approaches. results highlight superior capability MPOA, as evidenced various performance measures effectively segmenting Furthermore, metrics such peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), fitness values demonstrate that outperforms basic version POA methods. underscore significant impact RSA

Language: Английский

Citations

0
Multi-threshold medical image segmentation based on the enhanced walrus optimizer DOI
Jie Li,

Ruicheng Lu,

Biqing Zeng

et al.

The Journal of Supercomputing, Journal Year: 2025, Volume and Issue: 81(4)

Published: Feb. 17, 2025

Language: Английский

Citations

0
Hybrid Adaptive Crayfish Optimization with Differential Evolution for Color Multi-Threshold Image Segmentation DOI Creative Commons
Honghua Rao, Heming Jia, Xinyao Zhang

et al.

Biomimetics, Journal Year: 2025, Volume and Issue: 10(4), P. 218 - 218

Published: April 2, 2025

To better address the issue of multi-threshold image segmentation, this paper proposes a hybrid adaptive crayfish optimization algorithm with differential evolution for color segmentation (ACOADE). Due to insufficient convergence ability in later stages, it is challenging find more optimal solution optimization. ACOADE optimizes maximum foraging quantity parameter p and introduces an adjustment strategy enhance randomness algorithm. Furthermore, core formula (DE) incorporated balance ACOADE’s exploration exploitation capabilities better. validate performance ACOADE, IEEE CEC2020 test function was selected experimentation, eight other algorithms were chosen comparison. verify effectiveness threshold Kapur entropy method Otsu used as objective functions compared algorithms. Subsequently, peak signal-to-noise ratio (PSNR), feature similarity index measure (FSIM), structural (SSIM), Wilcoxon employed evaluate quality segmented images. The results indicated that exhibited significant advantages terms value, metrics, convergence, robustness.

Language: Английский

Citations

0
Application and Optimization of Intelligent Image Processing Technology in Cross-Border E-commerce DOI

W.G. Liang,

Jiahui Liang

Learning and analytics in intelligent systems, Journal Year: 2025, Volume and Issue: unknown, P. 401 - 412

Published: Jan. 1, 2025

Language: Английский

Citations

0
Optimized design and integration of an off-grid solar PV-biomass-battery hybrid energy system using an enhanced educational competition algorithm for cost-effective rural electrification DOI

Marwa M. Emam,

Hoda Abd El-Sattar, Essam H. Houssein

et al.

Journal of Energy Storage, Journal Year: 2025, Volume and Issue: 120, P. 116381 - 116381

Published: April 9, 2025

Language: Английский

Citations

0
Efficient bladder cancer diagnosis using an improved RIME algorithm with Orthogonal Learning DOI

Mosa E. Hosney,

Essam H. Houssein,

Mohammed R. Saad

et al.

Computers in Biology and Medicine, Journal Year: 2024, Volume and Issue: 182, P. 109175 - 109175

Published: Sept. 24, 2024

Language: Английский

Citations

3
An Improved Shuffled Frog-Leaping Algorithm to Solving 0–1 Knapsack Problem DOI Creative Commons

Jianhao Zhang,

Wei Jiang, Kang Zhao

et al.

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 148155 - 148166

Published: Jan. 1, 2024

To address the problems of slow convergence, low search accuracy, and easy fall into local optimum, generating a large number infeasible solutions when solving 0-1 Knapsack Problem, which makes it difficult to obtain optimal solution scheme, in this paper, we present greedy induced mutation method for locally solutions, namely, an improved Shuffled Frog Leaping Algorithm (Shuffled based on Greedy Mutation, SFLA-GA-M). First, proposed algorithm adjusts population generation individuals SFLA avoid thereby optimizing update strategy. Secondly, mechanism that incorporates both algorithms genetic is introduced enhance accuracy algorithm. Finally, ten classical Problem cases were selected prove feasibility robustness SFLA-GA-M by comparing with other two variants, are MDSFLA, DSFLA. Meanwhile, further verify performance SFLA-GA-M, KPs multi-dimensional test compared five algorithm, including: DEA, PSO, GA, BMA IFMA. The experimental results show has achieved stronger convergence stability displayed better efficiency superior global capability than IFMA large-sized Problem.

Language: Английский

Citations

2