Automated Malaria Diagnosis Using Microscopic Images

In accordance with the necessity, there is an increase in demand for medical images in diagnostic applications, the use of proper enhancement methods are inevitable. Medical imaging is a challenging field where robust and cost-effective approaches are yet to be developed for screening of diseases. Regular screening for Malaria is necessary since it can be a life-threatening disease to the group of people. Thus risk management can be done with pre-diagnosis. The identification of malarial parasites is usually done based on the symptoms of the patients. In this conventional method, there is limited access to experts in microbiology and pathology particularly in rural area practice and this restricts the diagnostic facilities. This paper presents a novel automatic diagnosis of malaria through microscopic images with the help of image processing. The paper deals with the existing systems for malarial screening and the detection methods of the disease. The proposed system quantifies and classifies the red blood cells infected by Plasmodium falciparum, Plasmodium vivax, Plasmodium ovale and Plasmodium malariae in thin blood smears. The experimentation was conducted in MATLAB in which image acquisition, pre-processing including segmentation, classification and a combination of other image processing techniques were performed.