Optimal Whole Slide Image Segmentation Using Generalized Normal Distribution Optimization

Authors

  • K.P. Shivamurthy Research Scholar, SSAHE, Tumakuru, India. Author
  • Dr. Raju.A. S Professor & Head, Department of Medical Electronics Engineering, SSIT, Tumakuru, India. Author

DOI:

https://doi.org/10.47392/IRJAEH.2024.0185

Keywords:

Histopathology Image Segmentation, Whole Slide Image Processing, Optimization Algorithm, Image Thresholding, Generalized Normal Distribution

Abstract

Whole slide image (WSI) segmentation is a crucial task aiding tumour and cancerous cell diagnosis. Generalized Normal Distribution Optimization (GNDO) algorithm is adopted for whole slide image segmentation based on thresholding in this paper. GNDO algorithm utilizes the generalized normal distribution's properties to determine the ideal thresholds for image segmentation. Through various metrics, the efficacy of GNDO in comparison to traditional Otsu thresholding methods is demonstrated. As demonstrated by the results, it can offer reliable and flexible solutions for different histopathology images.

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Published

2024-05-23

How to Cite

Optimal Whole Slide Image Segmentation Using Generalized Normal Distribution Optimization. (2024). International Research Journal on Advanced Engineering Hub (IRJAEH), 2(05), 1341-1347. https://doi.org/10.47392/IRJAEH.2024.0185

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