为了进一步用流域分割和图像信息融合的方法对于细胞形态的分析与识别打下基础，提出了利用形态学原理进行胃癌病理细胞图像灰度化边缘检测，并获得了实验性结果。通过与传统边缘检测方法进行结果对比，证明了形态学方法在医学病理细胞图像边缘检测研究的优势，同时结合图像纹理特点，对影响图像边缘检测的各种结构元素和灰度阈值进行了讨论。

Edge detection analysis for gastric tumor pathologic cell images by mathematical morphology is introduced here. The main purpose of the research is to lay a foundation of analysis and recognition for cellular morphology by the watershed segmentation and the information fusion of the images. In the paper, gray-scale edge detection methods of morphologic principle for the cell images are brought forward, whose experimental results are achieved. By comparing with the traditional edge detection methods, it is proved the advantages of the edge detection of mathematical morphology for the research of gastric tumor pathologic cell images. Combining with the texture features of investigated image, the paper has discussed the effect to the image edge detection with various configuration elements and gray-scale threshold values.