Automatic cell counting for phase‐contrast microscopic images based on a combination of Otsu and watershed segmentation method

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Abstract
Cell counting plays a vital role in biomedical researches. However, manual cell counting is time‐consuming, laborious, and low efficiency and has a high counting error rate problem. An automatic counting approach for Hela cells of phase‐contrast microscopic images is proposed based on the combination of Otsu and watershed segmentation methods to solve the mentioned issues. Firstly, image preprocessing is performed. Secondly, the Otsu method was used to obtain an automatic global optimal threshold for segmentation to achieve batch counting of images. Thirdly, the marker watershed was performed to separate adherent cells and to avoid over‐segmentation simultaneously. Finally, cells in phase‐contrast microscopic images were counted by detecting the numbers of connected domains in the binary image. Taking the manual counting result as the counting standard and MIS, INC, and ACC are used as evaluation indicators. The experimental results showed that the average values of MIS, INC, and ACC of the proposed method are only 3.31%, 3.49%, and 96.69%, respectively. Additionally, each cell image was counted only takes 0.65 s on averagely. To further test the performance of the proposed method, a comparative experiment was carried out by Image J, and the result shows that the proposed method has a better counting performance with a higher average accuracy of 96.55% to Image J with 93.39%.The proposed method for cell counting is simple, feasible, fast and high accurate, and it can be used as an effective method for cell counting of the phase‐contrast microscopic images.
Funding Information
  • National Natural Science Foundation of China (61605048)

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