Automatic Detection of Sickle cell in Red Blood cell using Watershed Segmentation

Abstract: Red Blood Corpuscles are the major cellular component of human blood which is responsible for gaseous exchange between living cell and external environment. In normal physiological condition, an RBC is circular in front view and biconcave in side view. In this paper image processing techniques applied on RBC cell to count the normal and abnormal cells using Watershed Segmentation. Then form factor calculated for each cell to differentiate between normal and abnormal cell. Also Contour plot of RBC cell drawn to highly visualize the RBC cell, Sickle cell, and Target Cell. Simulation of this technique is done on MATLAB 2013a.

Keywords: Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE), Red Blood Corpuscles (RBC), Sickle Cell Anemia (SCA), edge detection, Root Mean Square Error (RMSE).