Segmentation of Red Blood Cells - Deepa, TP; Reddy, N Sai Ahladitha; Santhoshi, K Jai; Priya, M; Lakshmi, N (International Journal of Computer Sciences and Engineering, 2025)
The study of abnormal cells is important to identify diseases like anemia, thalassemia and polycythemia. Cell features are important to identify abnormality in a given cell. The manual method used to identify abnormality of red blood cells is tedious, prone to human errors and time consuming. Hence, there is a need for fast and accurate system which can identify red blood cell abnormality and helps the doctor to quickly diagnose the diseases. Also, early detection of abnormality helps to prevent chronic diseases. This paper aims to develop such fast and accurate computer aided system which can automatically segment rbc in a given microscopic image. Further, the features of segmented cells are analyzed to detect abnormality. As the microscopic blood samples includes various cells like red blood cells, platelets, white blood cells, enzymes, biological debris, it is significant to segment only red blood cells by eliminating other unwanted cells in the given sample. So, this paper uses image segmentation technique to separate red blood cells in a given sample by eliminating white blood cells and platelets. These segmented cells are further used for feature extraction and classification.