Study On Image Detection Method Of Cervical Cytology Infected By Microorganism

This paper takes the liquid based thin layer of cervical microbial infection cells as the research object.In order to realize the general infection cells of cervical microbial detection, The microbial rapid positioning, infected cells of cervical position visual feature analysis and feature extraction is the key points. According to the combination of human visual perception and rough set theory and through the analysis of physical characteristics to the cells of cervical microbial infection, the model of microbial infection attribute is established. The cut set segmentation method is used to provide a uniform way and extract cervical microbial infection cell. Finally, the cell recognition and detection of microbial infections is realized with the classifier designed based on the rough set theory.The focus of this research is to analysis the vision consistency of cervical microbial infection cell and the visual distinction of its normal squamous epithelial cells,according to the knowledge and human visual perception of medical pathology from the perspective of visual perception and verify it with experiments.The specific research contents could be shown as follows :(1) The visual consistency of cervical microbial infection is analyzed from the perspective of visual perception. The result of experiments proves the consistency characteristics in color, intensity and area of consistency.(2) According to the consistency of the visual characteristics of the cervical microorganism infection, a model of the cell properties of cervical microbial infection is established. And the results of experiment shows the discrimination between cervical cells and normal squamous epithelial cells, which provides cervical cells and normal squamous epithelial cells.(3) According to the visual features of the cells infected by microorganisms, a new method of image segmentation based on multi cut sets is proposed, and Multi cut image segmentation model is set. and the reliability of the segmentation method is verified by experiments, To realize the rapid localization and extraction of the cells in the cervix of the uterus.(4) Based on rough set theory,by extracting the characteristic parameters of the microorganism infected cells, the intelligent identification to intelligent identification is achieved with the rough set classifier designed by attribute reduction rulesIn this paper, the characteristics of human visual perception is introduced and the visual characteristics of a large number of microbial infected cells is analyzed to describe the physical characteristics of cervical cells infected, from perspective of visual perception. The consistency of human visual perception is verified by the visual data,which provides an effective detection method for the detection of cervical microorganism infected cells. The experimental results shows that, the outline of infected cells of cervical microbial detection could be effectively realized by the proposed detection method of this paper.