Precise Segmentation of White Blood Cells by Using Multispectral Imaging Analysis Techniques

Abstract

Counting of different classes of white blood cells in bone marrow smears can give pathologists valuable information regarding various hematological disorders. For automation imaging analysis techniques, precise segmentation of white blood cells is quite challenging due to the complex contents in bone marrow smears. Far more different from traditional color imaging analysis methods, we introduced multispectral imaging techniques. After a high quality image was acquired, the spectrum of each pixel was directly fed into a trained support vector machine (SVM) for classification, and then morphological binary operations were performed to correct the small error-classified regions. Mass of experiments showed that the segmentation results are highly satisfactory and inspiring. It shows that the introduction of multispectral imaging analysis techniques into white blood cells detection is a success. Multispectral imaging analysis is a promising technique in biomedicine.