Segmentation of malaria parasites in peripheral blood smear images

Detection of malaria parasites in stained blood smears is critical for treatment of the disease. Automation of this process will help in reducing the time taken for diagnosis and the chance for human errors. However, the variability and artifacts in microscope images of blood samples pose significant challenges for accurate detection. A scheme based on HSV color space that segments Red Blood Cells and parasites by detecting dominant hue range and by calculating optimal saturation thresholds is presented in this paper. Methods that are less computation-intensive than existing approaches are proposed to remove artifacts. The scheme is evaluated using images taken from Leishman-stained blood smears. Sensitivity and specificity of the scheme are found to be 83% and 98% respectively.