Blood cell classification method based on hyperspectral data
一种基于超光谱的血细胞分类方法*

The goal of this paper was to classify blood cells based on hyperspectral data range from near infrared to visible light. Different from common classification method, the extracted features included not only gray information in flat images, but also plentiful spectral characteristics. As for the blood cell classification, the classifier was made up of genetic algorithm and neural network. Experimental results show that this means is effective on red cells and nucleolus of tumor cells. Compare to spectral data of 10 bands and data of 80 bands, hyperspectra can get better results at the cost of running time.