Identification of erythrocyte types in greyscale MGG images for computer-assisted diagnosis

Abstract

In the paper an algorithm for the recognition of erythrocytes is presented and experimentally evaluated. The objects of interest are localised and extracted from digital microscopic images, stained by means of the MGG (May-Grunwald-Giemsa) method in greyscale. The area covering a single red blood cell (RBC) is transformed from Cartesian to polar co-ordinates. Later, the two-dimensional Fourier transform is applied to the resultant image. Finally, the subpart of the spectrum is selected in order to represent an object. This description (Polar-Fourier Greyscale Descriptor) is matched with the templates represented in the same way. The smallest dissimilarity measure indicates the recognised erythrocyte type. When using this approach every RBC is investigated, and basing on the whole knowledge about the number of particular types of erythrocytes present in an image a diagnosis can be made. © 2011 Springer-Verlag.