Image investigation is a significant procedure in medical discipline during the infectious sickness and its harshness examination. If the reason of disease is recognized in its early stage, possible treatment can be planned to cure the patient. The proposed work implements a semi-automated technique to appraise images of Peripheral-Blood-Cell (PBC) recorded with digital microscope. The PBC is a proven procedure to investigate Leukocyte. This work integrates the Social-Group-Optimization plus Shonnon's Entropy (SGO+SE) based thresholding and Chan-Vese Segmentation (CVS) to extract the stained section from PBC picture. This tool is tested using the Leukocyte-Images for-Segmentation-Classification (LISC) by considering its RGB scale pictures. The advantage of this tool is confirmed with a comparative investigation between the extracted PBC segment and the ground-truth. This approach offers an enhanced image similarity measure (>90%) on the LISC dataset. This confirms that, this tool can be used to examine clinical PBC pictures.
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