[A technology research for diagnosis of mammographic masses based on content-based image retrieval]

In order to assist doctors in making the diagnosis of mammographic masses, a method is proposed in this paper. Twenty-two features are extracted from each queried region of interest (ROI). A k-nearest neighbor (KNN) algorithm is used to retrieve similar images from database, and further calculate the mutual information (MI) between the queried image and the images which are in the retrieval results, so as to improve the retrieval performance. Finally, the scheme takes the first nine images with the highest MI scores as the final retrieval results. With the purpose of providing available decision-making information of diagnostic aids, we compare and analyze three calculating methods of decision index. The experiment results show that this method is better than the method using KNN only, and this method improves the accuracy of diagnosis effectively.