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Proposes an image edge detection method based on multi-directional, multi-scale Top-hat operators, and apply the method to the edge detection and diagnosis of OSAHS (Obstructive Sleep Apnea Hypopnea Syndrome, OSAHS) early pathological images. Through the observation and analysis of the OSAHS early pathological images, considering the image Shapesand noise,construct multi-directional, multi-scale Top-hat operators, and they are used to enhance the contrast of images. Use morphological gradient to detect the edge. Then the ideal image edge is obtained by combining the edges of the image detected by each operator according to a certain weight, so that I can obtain relevant parameters of pathology images accurately, and then achieve electronic medical diagnosis. The processing results of OSAHS early pathological images including oral image, vocal cords oral image and inside nose image show that the operator proposed in this paper can make the edge information of the image more complete and accurate, compared with conventional edge operator, and edge closure of image is 97.67%, in the future can provide a solid foundation for electronic medical diagnosis.