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Multi-Objective Whole Slide Image Segmentation Using Nature Inspired Whale Optimization Algorithm

International Journal of Electrical and Electronics Engineering
© 2025 by SSRG - IJEEE Journal
Volume 12 Issue 9
Year of Publication : 2025
Authors : K P Shivamurthy, Raju A S
10.14445/23488379/IJEEE-V12I9P121
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How to Cite?

K P Shivamurthy, Raju A S, "Multi-Objective Whole Slide Image Segmentation Using Nature Inspired Whale Optimization Algorithm," SSRG International Journal of Electrical and Electronics Engineering, vol. 12,  no. 9, pp. 202-214, 2025. Crossref, https://doi.org/10.14445/23488379/IJEEE-V12I9P121

Abstract:

For precise histopathological image analysis and classification, segmentation is a critical step that must be carried out accurately. Segmentation aids early detection and diagnosis of tumor and cancerous cells. Machine learning and artificial intelligence processes play a vital role in image processing applications. In this proposed work, the nature-inspired Whale Optimization Algorithm is used for the segmentation of whole slide images through multi-objective image thresholding. The images are subjected to initial pre-processing to eliminate disturbance and enhancement, followed by the application of the best threshold value. Various histopathology images are examined to validate the efficiency and versatility of the proposed methodology. A Dice coefficient of 50.8, a Jaccard index of 51.33, a Precision of 51.22, a Sensitivity of 71.59, an Accuracy of 91.86, an F-measure of 50.76, and a Specificity of 71.17 were the average results obtained for the tested images using the proposed system. The outcomes are assessed with other common segmentation approaches, validating the algorithm.

Keywords:

Histopathology image, Image segmentation, Multi-objective optimization, Otsu thresholding, Whale optimization algorithm.

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