Feature extraction and analysis on X-ray image of Xinjiang Kazak Esophageal cancer by using gray-level histograms

Image feature extraction technology has been widely used in medical field, but there is no related research on image feature extraction of high morbidity of esophageal cancer in Xinjiang. In this paper, feature extraction based on gray-scale histograms was applied in X-ray barium angiogram in high morbidity of esophageal cancer in Xinjiang. For the X-ray barium angiogram, converting RGB image to the grayscale intensity image, through median filter to remove the image noise and using histogram equalization to enhance the contrast; then the gray-level histograms was used to get the features of the images, and the classification ability of features was evaluated by Bayes discriminant analysis. The result show that feature classification ability was different when classifying different images, which provides a new direction for the research of computer aided diagnosis system for the high incidence of Kazak esophageal cancer in Xinjiang Uygur Autonomous Region.