A Method of Leukocyte Segmentation Based on S Component and B Component Images

Abstract

A leukocyte segmentation method based on S component and B component images is proposed. Threshold segmentation operation is applied to get two binary images in S component and B component images. The samples used in this study are peripheral blood smears. It is easy tō nd from the two binary images that gray values are the same at every corresponding pixels in the leukocyte cytoplasm region, but opposite in the other regions. The feature shows that \IMAGE AND" operation can be employed on the two binary images to segment the cytoplasm region of leukocyte. By doing \IMAGE XOR" operation between cytoplasm region and nucleus region, the leukocyte segmentation can be retrieved e®ectively. The segmentation accuracy is evaluated by comparing the segmentation result of the proposed method with the manual segmentation by a hematologist. Experiment results show that the proposed method is of a higher segmentation accuracy and it also performs well when leukocytes overlap with erythrocytes. The average segmentation accuracy of the proposed method reaches 97.7% for segmenting¯ve types of leukocyte. Good segmentation results provide an important foundation for leukocytes automatic recognition.

Leukocyte nucleus segmentation method based on enhancing the saliency of saturation component

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Automatic counting method for complex overlapping erythrocytes based on seed prediction in microscopic imaging

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A fast auto-focusing method of microscopic imaging based on an improved MCS algorithm

“…Di®erent focused objects may lead to a little bit change for k. In the microscopic imaging detection for blood smear, there arē ve typical types of leukocyte such as neutrophil (Neu), lymphocyte (Lym), monocyte (Mon), eosinophil (Eos) and basophil (Bas) 17,18 as shown in Fig. 6.…”