Medical Image Retrieval Using Curvelet Transform And Diffusion Maps
While handling large images databases, effective and efficient image retrieval system is most definitely needed. The medical image retrieval is divided into: texture based image retrieval systems and Content Based Image Retrieval (CBIR) systems. The medical image retrieval is to identify various diseases that provides the detailed view of internal organs of the body. The aim of the medical image retrieval is to retrieve the similar images from the database according to the given query image. Generally, medical images have the problem of noises. We use de noising methods to remove noise from the images, while saving the other information and edges. To overcome the noise of images, we use the Curvelet features which improves the texture. Curvelet is a mathematical powerful tool for extracting features and tool of multi resolution analysis to define edges and singularities in curves. We also use diffusion maps, to extract the features of images reducing the dimensionality space of the input images. The method introduced consists of retrieving the medical images using Curvelet and Diffusion Maps (DM). The retrieval method will be able to detect various diseases effectively depending on the available database.