Extracting, Recognizing, and Counting White Blood Cells from Microscopic Figures by using Complex-Valued Neural Networks

Abstract

In this paper we present a method related to extracting white blood cells (WBCs) from blood microscopic figures and recognizing them and counting each kind of WBCs. In this method, first we extract the white blood cells from other blood cells by RGB color system's help. In continuance, by using the features of each kind of globules and their color scheme, we extract a normalized feature vector, and for classifying, we send it to a complex-valued back-propagation neural network. And at last, we send the results to the output in the shape of the quantity of each of white blood cells.