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What is WBC Segmentation via K-Means & Watershed about?

This paper presents a novel method for segmenting white blood cells (WBCs) from microscopic images using a combination of thresholding, k-means clustering, and modified watershed algorithms. The proposed approach includes three stages: segmentation of WBCs, extraction of nuclei, and separation of overlapping cells, achieving high precision and sensitivity in segmentation results. The method aims to assist pathologists in diagnosing blood-related diseases by automating the tedious process of WBC analysis.

Author

SANJAYKUMAR KINGE

Language

EN