Detection Of The Malarial Parasite Infected Blood Images By 3d-Analysis Of The Cell Curved Surface

In blood samples, if the red corpuscles of vertebrates are infected by malarial parasites, they will have a specific shape which can identify their presence. Recent research has suggested that the shape of the affected red blood cells can be detected using the 2D moments of the image of the infected cell. Since real blood cells are 3D in nature, the image has to be treated as 3D. We have extended this 2D approach to 3D image processing for detecting and classifying malarial parasites in images of Giemsa stained blood slides, by evaluating the surface of the parasitaemia in the infected blood, which will yield better accuracy to the diagnosis. The primary aim is to detect the blood cells infected by malarial parasites based on the 3D-statistical approach of evaluating the curved surface area of cell structure by computing the 3D moments of the image.