Abstract: To detect the morphology, proliferation, and differentiation of human cells quickly and accurately, an efficient adaptive cell image segmentation method is proposed. First, the image of saturation with obvious characteristics is extracted from the Hue,Saturation Value (HSV) channel of the image, and then, morphological reconstruction, H-minima technology, and image enhancement technology are used to perform gradient correction on the image of saturation. After the gradient of the image is corrected, the watershed algorithm is used to perform segmentation. Next, the segmentation result is merged to obtain the background, cell, and nucleus according to the gray level consistency of the original image. Finally, post-morphological processing is used to remove the false noise in the merged result and flatten the edge of the region. The results of the segmentation test on cell images show that the accuracies of cell and cell nucleus segmentation are 0.978 8 and 0.967 7, respectively. The Dice coefficients are 0.938 8 and 0.937, which realizes the accurate segmentation of medical micro cell images.

Key words: watershed, morphological reconstruction, H-minima, regional merger, cell image