Overlapping Cervical Cell Image Segmentation Based on Bottleneck Detection and Watershed Algorithm / 中国医疗器械杂志

This study proposes an image segmentation method based on bottleneck detection and watershed algorithm to solve the problem of overlapping cervical cell image. First, we use polygon approximation to get all feature points on the cell contour and then use bottleneck detection and ellipse fitting to obtain the correct split point pairs. Therefore, the approximate range of the overlapping region was determined. The watershed algorithm was used to obtain the internal boundary information for the gradient image of the region. Finally, the segmentation results of the overlapped cells were obtained by superimposing with the outer contour. The experimental results show that this algorithm can segment the contour of a single cell from the overlapping cervical cell images with good accuracy and integrity. The segmentation result is close to that of doctors' manual marking, and the segmentation result is better than other existing algorithms.

A new modified watershed algorithm for image segmentation in cervical cancer cell adhesion / 军事医学

Objective To investigate an effective algorithm for image segmentation in cervical cancer cell adhesion , which enables accurate segmentation of the contour of adherent cells .Methods The images of target cells were extracted from the background area using level set methods , normalized with minimum values of transformation algorithms ,and multi-plied by the gradient image points in the region of interest ( ROI) to inhibit the undesired gradient information before the im-ages of adherent cells were segmented using labeled watershed algorithm .Results and Conclusion Compared to conven-tional watershed segmentation methods , this algorithm is not only effective in image segmentation of adherent cervical cancer cells with uneven staining and more accurate segmentation lines established around the contours of adherent cells , but of high clinical value .