New Approch to Red Blood Cell Classification Using Morphological Image Processing

Abstract

Blood disorders can cause morphological changes in mature red blood cells so by investigating blood smears morphologically, we can study and distinguish blood diseases such as anemias. On the other hand, because most of the available methods are manual, expensive, time-consuming and depend on the experts expertise so for improving detection rate and increasing its accuracy, a method of automated analysis for the rapid classification of large numbers of red cells from individual specimens has been developed. According to this method which is based on digital image processing, several features relating to shape, internal central pallor configuration of red cells and their circularity and elongation have been extracted and with the help of a decision logic all those various types of red blood cells were classified into 12 categories. According to the obtained results, diagnosis of blood disorders such as iron deficiency anemia, the anemia of chronic disease, β-thalassemia trait, sickle cell anemia, hemoglobin C disease, intravascular hemolysis, hereditary elliptocytosis, hereditary spherocytosis and megaloblastic anemia due to folic acid deficiency can be possible.