Horizontal and vertical search artificial bee colony for image segmentation of COVID-19 X-ray images. (March 2022)

• Record Type: Journal Article
• Authors: Su, Hang; Zhao, Dong; Yu, Fanhua; Heidari, Ali Asghar; Zhang, Yu; Chen, Huiling; Li, Chengye; Pan, Jingye; Quan, Shichao
• Is Part Of: Computers in biology and medicine. Volume 142(2022)
• Publication Date: 2022-03
• Subjects: Disease diagnosis -- Multi-threshold image segmentation -- Meta-heuristic -- COVID-19 -- Swarm-intelligence; Medicine -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; 610.285
• DOI: 10.1016/j.compbiomed.2021.105181
• Languages: English
• ISSNs: 0010-4825

Abstract

Abstract: The artificial bee colony algorithm (ABC) has been successfully applied to various optimization problems, but the algorithm still suffers from slow convergence and poor quality of optimal solutions in the optimization process. Therefore, in this paper, an improved ABC (CCABC) based on a horizontal search mechanism and a vertical search mechanism is proposed to improve the algorithm's performance. In addition, this paper also presents a multilevel thresholding image segmentation (MTIS) method based on CCABC to enhance the effectiveness of the multilevel thresholding image segmentation method. To verify the performance of the proposed CCABC algorithm and the performance of the improved image segmentation method. First, this paper demonstrates the performance of the CCABC algorithm itself by comparing CCABC with 15 algorithms of the same type using 30 benchmark functions. Then, this paper uses the improved multi-threshold segmentation method for the segmentation of COVID-19 X-ray images and compares it with other similar plans in detail. Finally, this paper confirms that the incorporation of CCABC in MTIS is very effective by analyzing appropriate evaluation criteria and affirms that the new MTIS method has a strong segmentation performance. Highlights: This paper proposes an improved artificial bee colony optimization (CCABC). CCABC is applied to COVID-19 multi-threshold image segmentation based on 2D histogram. CCABC has a great improvement in the ability to search for the optimal solution. The segmentation performance of CCABC is verified by comparison with well-known algorithms.