Pre-processing, Extraction and Recognition of Binary Erythrocyte Shapes for Computer-Assisted Diagnosis Based on MGG Images

The paper presents an approach for computer-assisted diagnosis of some diseases (e.g. anaemia, malaria), which are caused by deformations of erythrocyte shapes. In the method firstly the thresholding of the input MGG image is performed, using modified thresholding based on fuzzy measures. Secondly, every cell is localised and extracted. Only the red blood cells are taken for later processing. Using the template matching approach and shape description algorithm every extracted erythrocyte is assigned to one of the twelve classes. Basing on the knowledge about the number of particular unaffected and affected red blood cells the diagnosis can be made. Hence, the possibilities of automatic diagnosis are discussed to stress the potential application of the method.