Automatic cell counting for phase‐contrast microscopic images based on a combination of Otsu and watershed segmentation method. Issue 1 (9th August 2021) - Lin, Yuefei; Diao, Yong; Du, Yongzhao; Zhang, Jianguang; Li, Ling; Liu, Peizhong
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. Abstract : There are many challenges for cell counting of the microscopic images, such as the blurred contour, slender structures, and adhesion of cells. However, the overlapping and adhering cells in the image are tend to be recognized as only one cell by the counting software IncuCyte ZOOM. Image J, which is generally widely used in biomedical research for counting, has relatively low efficiency as various module selections and parameter adjustments are required in various module selections and parameter adjustments are required during counting. In this paper, an automatic counting approach for Hela cells of phase‐contrast microscopic images is proposed based on the combination of Otsu and watershed segmentation methods which is simple, efficient, low‐cost, and has an average accuracy of 96.69%. An automatic fast counting method for dense Hela cells designed explicitly for phase contrast microscopy is proposed. The method of stepwise segmentation using Otsu and watersheds solves the problem of connection interference in cell segmentation and improves the segmentation effect. Established a cell counting sample library of phase‐contrast micrographs of Hela cells. Realize batch counting, cropping and saving of cell images.