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. 2019 Jun 11:2019:3072498.
doi: 10.1155/2019/3072498. eCollection 2019.

Quick Leukocyte Nucleus Segmentation in Leukocyte Counting

Yapin Wang  1 , Yiping Cao  1
Affiliations

Quick Leukocyte Nucleus Segmentation in Leukocyte Counting

Yapin Wang et al. Comput Math Methods Med. .

Abstract

The leukocyte nucleus quick segmentation is one of the key techniques in leukocyte real-time online scanning of human blood smear. We propose a quick leukocyte nucleus segmentation method based on the component difference in RGB color space. By analyzing the captured microscopic images of the peripheral blood smears from the autoscanning microscope, it is found that the difference values between B component and G component (B - G values) in the regions of the leukocyte nuclei and the platelets are much bigger than those in the other regions, even in the regions including the stains. So, the B - G values can segment the leukocyte nuclei and the platelets with an appropriate empirical threshold because the platelets are much smaller than the leukocyte nuclei, so the leukocyte nuclei can be segmented by size filtering. Also, only an 8 bit subtraction operation is performed for the B - G values, and it can improve the leukocyte nucleus segmentation speed significantly. Experimental results show that the proposed method performs well for the five types of leukocyte segmentation with a quick speed. It is very suitable for the real-time peripheral blood smear autoscanning test application. In addition, the five types of leukocytes can be counted accurately.

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Figures

Figure 1
Figure 1
The R, G, and B components' cutaway views for captured leukocyte images at different conditions. (a) The captured leukocyte image 1. (b) The captured leukocyte image 2. (c) The captured leukocyte image 3. (d) The R, G, and B components' cutaway views on AA′ of (a). (e) The R, G, and B components' cutaway views on BB′ of (b). (f) The R, G, and B components' cutaway views on CC′ of (c). (g) The B − G component's cutaway view on AA′ of (a). (h) The B − G component's cutaway view on BB′ of (b). (i) The B − G component's cutaway view on CC′ of (c).
Figure 2
Figure 2
The R, G, and B components' cutaway views for captured leukocyte images with stains at different conditions. (a) The leukocyte captured image 1. (b) The leukocyte captured image 2. (c) The leukocyte captured image 3. (d) The R, G, and B components' cutaway views on AA′ of (a). (e) The R, G, and B components' cutaway views on CC′ of (b). (f) The R, G, and B components' cutaway views on EE′ of (c). (g) The B − G component's cutaway view on AA′ of (a). (h) The B − G component's cutaway view on CC′ of (b). (i) The B − G component's cutaway view on EE′ of (c). (j) The R, G, and B components' cutaway views on BB′ of (a). (k) The R, G, and B components' cutaway views on DD′ of (b). (l) The R, G, and B components' cutaway views on FF′ of (c). (m) The B − G component's cutaway view on BB′ of (a). (n) The B − G component's cutaway view on DD′ of (b). (o) The B − G component's cutaway view on FF′ of (c).
Figure 3
Figure 3
The connected region labeling image. (a) The multileukocyte captured image. (b) The B-G image. (c) The binarization image. (d) The segmented nucleus. (e) The connected region labeled image of (d).
Figure 4
Figure 4
Some of the distinguished artifacts. (a) Artifact 1. (b) Artifact 2. (c) Artifact 3. (d) Artifact 4. (e) Artifact 5.
Figure 5
Figure 5
The segmentation process. (a) The captured leukocyte images. (b) The B-G images. (c) The binarization images. (d) The segmentation results. (e) The leukocyte nucleus location.
Figure 6
Figure 6
The blood smears and the autoscanning system experimental device. (a) Blood smears. (b) Autoscanning system experimental device.
Figure 7
Figure 7
The leukocyte autoscanning test results for different blood smears at different conditions. (a) The extraction leukocyte images of blood smear sample 1. (b) The extraction leukocyte images of blood smear sample 2.
Figure 8
Figure 8
Clumped leukocytes and the segmentation result. (a) Clumped leukocytes. (b) Segmentation result. (c) Segmented image 1. (d) Segmented image 2. (e) Segmented image 3. (f) Segmented image 4. (g) Segmented image 5. (h) Segmented image 6. (i) Segmented image 7.
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