Medical Image Retrieval Relevance Feedback Method Based on Weighted Mahalanobis Distance

In order to solve the "semantic gap" between the underlying physical characteristics and high—level semantic image retrieval for medical digital image,a method of combining a dynamic weight adjustment and the weighted Mahalanobis distance was proposed to feedback.The search strategy was modified to improve the retrieval recall ratio and precision ratio.The method overcame the problems of the Euclidean distance in the calculation of the similarity of feature vectors between the property—related issues,reduced redundancy and improved the retrieval accuracy.The experimental results showed that this method could effectively use user' s feedback to improve retrieval performance.