A review on automated diagnosis of malaria parasite in microscopic blood smears images

Malaria is a life-threatening disease caused by parasite of genus plasmodium, which is transmitted through the bite of infected Anopheles. A rapid and accurate diagnosis of malaria is demanded for proper treatment on time. Mostly, conventional microscopy is followed for diagnosis of malaria in developing countries, where pathologist visually inspects the stained slide under light microscope. However, conventional microscopy has occasionally proved inefficient since it is time consuming and results are difficult to reproduce. Alternate techniques for malaria diagnosis based on computer vision were proposed by several researchers. The aim of this paper is to review, analyze, categorize and address the recent developments in the area of computer aided diagnosis of malaria parasite. Research efforts in quantification of malaria infection include normalization of images, segmentation followed by features extraction and classification, which were reviewed in detail in this paper. At the end of review, the existent challenges as well as possible research perspectives were discussed.