Malaria Detection Using Image Processing and Deep Learnin

Malaria is caused by parasites called Plasmodium, transmitted through mosquito bites. Malaria parasites are micro-organisms that belong to the genus Plasmodium. Microscopical analysis of stained blood cells is the standard diagnostic method for malaria. A drop of blood can be counted under a microscope to assess the number of contaminated Red Blood Corpuscles (RBC cells). The study of the slide requires the full attention of an experienced specialist. This takes a lot of effort and time. In this research, we build a novel image processing system to detect and quantify plasmodium parasites on a blood smear slide, and we use this approach to guide the development of a Deep Learning algorithm that can learn to identify and categorize different types of diseased cells.