Abstract
White blood cell (WBC) segmentation, which is important for cytometry, is a challenging issue because of the morphological diversity of WBCs and the complex and uncertain background of blood smear images. This paper proposes a novel method for the nucleus and cytoplasm segmentation of WBCs for cytometry. A color adjustment step was also introduced before segmentation. Color space decomposition and k-means clustering were combined for segmentation. A database including 300 microscopic blood smear images were used to evaluate the performance of our method. The proposed segmentation method achieves 95.7% and 91.3% overall accuracy for nucleus segmentation and cytoplasm segmentation, respectively. Experimental results demonstrate that the proposed method can segment WBCs effectively with high accuracy.
Highlights
The immune system, which is the third line of defense of the human body, protects the body from viruses, bacteria, and pathogens
This paper proposed a new White blood cell (WBC) segmentation method by using color-space-based k-means clustering
A novel color adjustment method was applied before segmentation, improving the segmentation accuracy
Summary
The immune system, which is the third line of defense of the human body, protects the body from viruses, bacteria, and pathogens. Image analysis identifies abnormal cells and adopts the diagnosis experience summarized by pathologists This method uses the high resolution and flexible extracted features of computer vision to improve work efficiency and accuracy. Proposed a WBC segmentation method by using stepwise merging rules based on mean-shift clustering and boundary removal rules with GVF snake. Sadeghian et al [12] presented a WBC segmentation framework that segments the cytoplasm by using GVF snake This framework identifies the cytoplasm by applying Zack thresholding [13] to a gray image with the nucleus region removed. Saraswat et al surveyed the current situation of WBC segmentation and indicated that the results of WBC segmentation are still not acceptable and need to be improved They pointed out that the presence of artifacts, shape variations in the WBCs, and overlapped cells are the major problems and must be focused on [8]. Aiming at the first two major problems, we present a novel, effective technique with good performance and robustness for WBC segmentation
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