抄録
Measuring the proportion of white blood cells is effective for estimating the source of the disease or for observing the progress of the disease. However, it takes long time by hand and requires the specialized knowledge, thereby the method for automatically classifying cells is needed. We propose a classification of white blood cells based on neural network in this paper. Nine parameters of area, shape and color information are extracted from a microscopic image of cells. These parameters are used as inputs for neural network classifier. Experimental results show that our proposed method can classify cells with high accuracy.
