Image processing-based diagnosis of sickle cell anemia in erythrocytes

Red Blood Corpuscles (RBC) constitutes the main cellular element of human blood. They are gaseous exchangers between living cell and external environment. In normal physiological state, RBC has circular shape in front view and biconcave shape in side view. RBCs take the sickle shape with person infected with cell anemia. Based on such different shapes, the work objective is to count the numbers of normal and abnormal RBC cells using two image processing techniques; circular Hough transform and watershed segmentation. Such counting is practically important in assessing the level of anemia disease danger. The processing Code of this technique is done on MATLAB 2015a.