Whale Optimizer-Based Clustering for Breast Histopathology Image Segmentation

Swarnajit Ray, Arunita Das, Krishna Gopal Dhal, Jorge Gálvez and Prabir Kumar Naskar
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Swarnajit Ray: Maulana Abul Kalam Azad University of Technology, India
Arunita Das: Midnapore College (Autonomous), India
Krishna Gopal Dhal: Midnapore College (Autonomous), India
Jorge Gálvez: Universidad de Guadalajara, Mexico
Prabir Kumar Naskar: Government College of Engineering and Textile Technology, Serampore, India

International Journal of Swarm Intelligence Research (IJSIR), 2022, vol. 13, issue 1, 1-29

Abstract: Breast histopathology image segmentation is a complex task due to indiscernibly correlated and noisy regions of interest. Breast histopathological images are composed of different types of cells. Some of these cells can be harmful for humans due to the presence of cancer. Under such circumstances, many segmentation techniques for automatic detection of cancer cells have been proposed considering clustering schemes. However, such clustering methodologies are sensitive to initial cluster centers, which promote false-positive solutions. This paper presents the use of the Whale Optimization Algorithm (WOA) for proper clustering segmentation of breast histopathological images to overcome clustering issues. Also, a rigorous comparative study is conducted among the proposed approach and several state-of-art Nature-Inspired Optimization Algorithms (NIOAs) and traditional clustering techniques. The numerical results indicate that the proposed approach outperforms the other utilized clustering methods in terms of precision, robustness, and quality of the segmented outputs.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jsir00:v:13:y:2022:i:1:p:1-29

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