Study On The Cell Classification And Recongnition Technigues

At present, medical workers mainly make pathological diagnosis through morphological observing to the section of cell tissue under microscope, and draw conclusion by experience. This kind of method is mainly qualitative and lack of objectivity. With the development of the technology, it is necessary to use the computer information technology to promote the pathological diagnosis to be more automatic and scientific.In view of the above mentioned problem, the author adopts information technology such as image processing and pattern recognition to research into the method of automatic analysis and classification. In accordance with the difficulty in medical image analysis (for example, the background of microimage of section is complicated and is difficult to be segmented.), the paper puts forward two kinds of segmentation methods based on standardized colorful space and RGB and HSV colorful model. First is the true-color segmentation using the method about eigenvector space cluster in pattern recognition. Second is the threshold segmentation adopting the biggest class separation variance and HSV model. This two kinds of methods make a good use of the information supplied by multiple-dimensional feature space and enhance the accuracy of segmentation. The paper further discusses the technique about measuring the shape and chroma of cell. On the basis of the existed technology, the paper perfects the arithmetic of target recognition and contour tracking and enables it to measure several kinds of parameters. The paper also brings forward several indexes to measure cells, which is of instructive meaning to cell segmentation. On the basis of experiments, the author presents a effective index to distinguish abnormal cells from normal ones and examines the method of cell classification. Above all, the paper puts forward a way of automatic detection of microimage of cell and lays a good foundation for a further study.