A New Semantic Annotation Method for Chest X-Ray Images

For the purpose of taking good use of the diagnosis obtained from medical experts and improving the accuracy of chest X-ray images retrieval, the lung fields are segmented and interested regions are marked off on the basis of chest X-ray images having been processed previously; the Gray Difference Statistics is used to indicate the texture feature of each region. Using the K-nearest neighbor classifier, the texture features are mapped respectively to the standard image classes pre-described by the experts, thus it realizes the semantic annotation of regions in the whole image. This method can not only narrow the semantic gap between the low-level features and the high-level semantics of images effectively, but also has an active effect on improving the efficiency of medical diagnosis.