Enhanced White Blood Cell and Platelet Segmentation: A Particle Swarm Optimization-based Chromaticity approach DOI

A.N. Senthilvel,

M. Krishnaveni,

Subashini Parthasarathy

et al.

Pertanika journal of science & technology, Journal Year: 2025, Volume and Issue: 33(3)

Published: April 22, 2025

Microscopic image examination is essential for medical diagnostics to identify anomalies using cell counts based on morphology. Sickle Cell Disease (SCD) an inherited blood condition characterized by defective hemoglobin, leading severe anemia and complications. Detecting sickle cells in smears essential, but the presence of White (WBCs) platelets often leads miscounting as they are classified incorrectly red (RBCs). This study proposed approach segmenting WBCs resembling human color recognition process differentiate regions accurate identification. First, RGB space converted RG chromaticity locate with high pixel chromatic variance. Parametric segmentation applied images appropriate channel probability distribution values. The optimal threshold values have been determined Particle Swarm Optimization (PSO) dynamically narrowing search obtained through manual experimentation ranging from 0.001 1. systematic effectively identifies segments WBCs, ensuring that overlapping accurately segmented. Compared state-of-the-art techniques, achieved accuracy 96.32 %, 96.97% sensitivity, 96.96 % precision 97.46% F- score pixel-wise platelets.

Language: Английский

Enhanced White Blood Cell and Platelet Segmentation: A Particle Swarm Optimization-based Chromaticity approach DOI

A.N. Senthilvel,

M. Krishnaveni,

Subashini Parthasarathy

et al.

Pertanika journal of science & technology, Journal Year: 2025, Volume and Issue: 33(3)

Published: April 22, 2025

Microscopic image examination is essential for medical diagnostics to identify anomalies using cell counts based on morphology. Sickle Cell Disease (SCD) an inherited blood condition characterized by defective hemoglobin, leading severe anemia and complications. Detecting sickle cells in smears essential, but the presence of White (WBCs) platelets often leads miscounting as they are classified incorrectly red (RBCs). This study proposed approach segmenting WBCs resembling human color recognition process differentiate regions accurate identification. First, RGB space converted RG chromaticity locate with high pixel chromatic variance. Parametric segmentation applied images appropriate channel probability distribution values. The optimal threshold values have been determined Particle Swarm Optimization (PSO) dynamically narrowing search obtained through manual experimentation ranging from 0.001 1. systematic effectively identifies segments WBCs, ensuring that overlapping accurately segmented. Compared state-of-the-art techniques, achieved accuracy 96.32 %, 96.97% sensitivity, 96.96 % precision 97.46% F- score pixel-wise platelets.

Language: Английский

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