White Blood Cell Image Segmentation based on Color Component Combination and Contour Fitting

Author(s): Chuansheng Wang, Hong Zhang*, Zuoyong Li*, Xiaogen Zhou, Yong Cheng*, Rongyan Chen.

Journal Name: Current Bioinformatics

Volume 15 , Issue 5 , 2020

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Background: White blood cell (WBC) image segmentation plays a key role in cell morphology analysis. However, WBC segmentation is still a challenging task due to the diversity of WBCs under different staining conditions.

Objective: In this paper, we propose a novel WBC segmentation method based on color component combination and contour fitting to segment WBC images accurately.

Method: Specifically, the proposed method first uses color component combination and image thresholding to achieve nucleus segmentation, then uses a color prior to remove image background, and extracts the initial WBC contour via Canny edge detection, and finally judges and closes the unclosed WBC contour by contour fitting. Accordingly, cytoplasm segmentation is achieved by subtracting the nucleus region from the WBC region.

Results: Experimental results on 100 WBC images under rapid staining condition and 50 WBC images under standard staining condition showed that the proposed method improved segmentation accuracy of white blood cells under rapid and standard staining conditions.

Conclusion: The proposed color component combination and contour fitting is effective in WBC segmentation task.

Keywords: White blood cell (WBC) segmentation, color component combination, color prior, image background removal, Canny edge detection, contour fitting.

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Article Details

Year: 2020
Page: [463 - 471]
Pages: 9
DOI: 10.2174/1574893614666191017102310
Price: $95

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