Open Access

ARTICLE

Marine Predators Algorithm with Deep Learning-Based Leukemia Cancer Classification on Medical Images

Sonali Das¹, Saroja Kumar Rout², Sujit Kumar Panda¹, Pradyumna Kumar Mohapatra³, Abdulaziz S. Almazyad⁴, Muhammed Basheer Jasser^5,6,*, Guojiang Xiong⁷, Ali Wagdy Mohamed^8,9

1 Department of Computer Science & Engineering, Gandhi Institute for Technology, BPUT, Bhubaneswar, 752054, India
2 Department of Information Technology, Vardhaman College of Engineering (Autonomous), Hyderabad, 501218, Telangana, India
3 Department of Electronic & Communication Engineering, Vedang Institute of Technology, Bhubaneswar, 752010, India
4 Department of Computer Engineering, College of Computer and Information Sciences, King Saud University, Riyadh, 11543, Saudi Arabia
5 Department of Computing and Information Systems, School of Engineering and Technology, Sunway University, Jalan Universiti, Bandar Sunway, Selangor Darul Ehsan, 47500, Malaysia
6 Research Centre for Human-Machine Collaboration (HUMAC), School of Engineering and Technology, Sunway University, Jalan Universiti, Bandar Sunway, Selangor Darul Ehsan, 47500, Malaysia
7 Guizhou Key Laboratory of Intelligent Technology in Power System, College of Electrical Engineering, Guizhou University, Guiyang, 550025, China
8 Operations Research Department, Faculty of Graduate Studies for Statistical Research, Cairo University, Giza, 12613, Egypt
9 Applied Science Research Center, Applied Science Private University, Amman, 11931, Jordan

* Corresponding Author: Muhammed Basheer Jasser. Email:

(This article belongs to the Special Issue: Advances in Swarm Intelligence Algorithms)

Computer Modeling in Engineering & Sciences 2024, 141(1), 893-916. https://doi.org/10.32604/cmes.2024.051856

Received 17 March 2024; Accepted 19 June 2024; Issue published 20 August 2024

Abstract

In blood or bone marrow, leukemia is a form of cancer. A person with leukemia has an expansion of white blood cells (WBCs). It primarily affects children and rarely affects adults. Treatment depends on the type of leukemia and the extent to which cancer has established throughout the body. Identifying leukemia in the initial stage is vital to providing timely patient care. Medical image-analysis-related approaches grant safer, quicker, and less costly solutions while ignoring the difficulties of these invasive processes. It can be simple to generalize Computer vision (CV)-based and image-processing techniques and eradicate human error. Many researchers have implemented computer-aided diagnostic methods and machine learning (ML) for laboratory image analysis, hopefully overcoming the limitations of late leukemia detection and determining its subgroups. This study establishes a Marine Predators Algorithm with Deep Learning Leukemia Cancer Classification (MPADL-LCC) algorithm on Medical Images. The projected MPADL-LCC system uses a bilateral filtering (BF) technique to pre-process medical images. The MPADL-LCC system uses Faster SqueezeNet with Marine Predators Algorithm (MPA) as a hyperparameter optimizer for feature extraction. Lastly, the denoising autoencoder (DAE) methodology can be executed to accurately detect and classify leukemia cancer. The hyperparameter tuning process using MPA helps enhance leukemia cancer classification performance. Simulation results are compared with other recent approaches concerning various measurements and the MPADL-LCC algorithm exhibits the best results over other recent approaches.

---

Keywords

---