The invention discloses a mammary glandular cell segmentation method based on a multi-scale growth and double-strategy adhesion-removing model. The method comprises the following steps: firstly, inputting a mammary glandular tissue image and converting the image into a gray image; secondly, enhancing the contrast ratio; thirdly, carrying out cell positioning by using wavelet decomposition; fourthly, carrying out multi-scale region growth; fifthly, realizing primary segmentation of a cell region through voting and selecting; sixthly, judging whether the segmented region has cell adhesion or not; if the cell adhesion does not exist, determining that the segmented region is a single cell region, and outputting a segmentation result; if the cell adhesion exists, determining that the segmented region is an adhesion region, and carrying out adherent cell segmentation; and finally, carrying out adherent cell segmentation by using the double-strategy adhesion-removing model constructed by morphological corrosion-expansion operation and a corner detection segmentation algorithm until all the cells are segmented. By virtue of the method, the influences on mammary glandular cell segmentation, caused by a complicated background of a mammary glandular tissue slice image, are effectively inhibited; and the identification precision of an adherent cell segmentation line is improved and the segmentation precision of the adherent cells is further improved.