Абстрактный

METHOD FOR BLOOD CELL SEGMENTATION

Prof. Samir K. Bandyopadhyay

AbstractThe analysis of blood cells in microscope images can provide useful information concerning the health of patients; however, manual classification of blood cells is time-consuming and susceptible to error due to the different morphological features of the cells. Therefore, a fast and automated method for identifying the different blood cells is required. In this paper, we propose a method to segment nucleus and cytoplasm of white blood cells (WBC). In this work, we segments cell images with varying background and illumination condition is designed. The results of segmentation show the better performance in comparison to the conventional methods. Experimental results suggest that the proposed method performs well in identifying blood cell types regardless of their irregular shapes, sizes, and orientation.