Boosted Nutcracker optimizer and Chaos Game Optimization with Cross Vision Transformer for medical image classification

Ahmed F. Mohamed; Amal Saba; Mohamed K. Hassan; Hamdy.M. Youssef; Abdelghani Dahou; Ammar H. Elsheikh; Alaa A. El-Bary; Mohamed Abd Elaziz; Rehab Ali Ibrahim

Egyptian Informatics Journal (Jun 2024)

Boosted Nutcracker optimizer and Chaos Game Optimization with Cross Vision Transformer for medical image classification

Ahmed F. Mohamed,
Amal Saba,
Mohamed K. Hassan,
Hamdy.M. Youssef,
Abdelghani Dahou,
Ammar H. Elsheikh,
Alaa A. El-Bary,
Mohamed Abd Elaziz,
Rehab Ali Ibrahim

Affiliations

Ahmed F. Mohamed: Industrial Engineering Department, College of Engineering and Architecture, Umm Al-Qura University, Makkah 21955, Saudi Arabia
Amal Saba: Department of Cell Biology, Faculty of Medicine, Tanta University, Tanta 31527, Egypt
Mohamed K. Hassan: Mechanical Engineering Department, College of Engineering and Architecture, Umm Al-Qura University, Makkah 21955, Saudi Arabia
Hamdy.M. Youssef: Mechanical Engineering Department, College of Engineering and Architecture, Umm Al-Qura University, Makkah 21955, Saudi Arabia
Abdelghani Dahou: School of Computer Science and Technology, Zhejiang Normal University, Jinhua 321004, China; Mathematics and Computer Science Department, University of Ahmed DRAIA, 01000, Adrar, Algeria
Ammar H. Elsheikh: Department of Production Engineering and Mechanical Design, Faculty of Engineering, Tanta University, Tanta, 31527, Egypt; Department of Industrial and Mechanical Engineering, Lebanese American University, Byblos 13-5053, Lebanon
Alaa A. El-Bary: Basic and Applied Science Institute, Arab Academy for Science, Technology and Maritime Transport, P.O. Box 1029, Alexandria, Egypt; National Committee for Mathematics, Academy of Scientific Research and Technology, Egypt; Council of Future Studies and Risk Management, Academy of Scientific Research and Technology, Egypt
Mohamed Abd Elaziz: Department of Mathematics, Faculty of Science, Zagazig University, Zagazig, 44519, Egypt; Faculty of Computer Science and Engineering, Galala University, Suze 435611, Egypt; Artificial Intelligence Research Center (AIRC), Ajman University, Ajman 346, United Arab Emirates; Department of Electrical and Computer Engineering, Lebanese American University, Byblos 13-5053, Lebanon; MEU Research Unit, Middle East University, Amman 11831, Jordan; Corresponding author at: Department of Mathematics, Faculty of Science, Zagazig University, Zagazig, 44519, Egypt.
Rehab Ali Ibrahim: Department of Mathematics, Faculty of Science, Zagazig University, Zagazig, 44519, Egypt

Journal volume & issue: Vol. 26
p. 100457

Abstract

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This paper presents an alternative breast cancer classification method based on enhancing the efficiency of the Nutcracker optimizer (NO) algorithm using Chaos Game Optimization (CGO). In addition, we use the Cross Vision Transformer to extract features from breast images. After that, the relevant features are allocated using the modified version of NO based on CGO. This modification aims to enhance the exploration ability of the NO algorithm to discover the region of a feasible solution (an optimal subset of features). The performance of the developed model is validated by using twelve functions from the CEC2022 benchmark and comparing the results with traditional CGO and NO algorithms. In addition, to assess the applicability of the developed technique, a set of three datasets, and the results were compared with other techniques. The results illustrate the high ability of the developed method to enhance the detection of breast cancer and find the optimal solution of CEC2022 functions according to different performance measures.

Published in Egyptian Informatics Journal

ISSN: 1110-8665 (Print)
Publisher: Elsevier
Country of publisher: Netherlands
LCC subjects: Science: Mathematics: Instruments and machines: Electronic computers. Computer science
Website: http://www.journals.elsevier.com/egyptian-informatics-journal/

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