Medical Image Retrieval Using Biorthogonal Spline Wavelet

An image retrieval system is a computer system for browsing, searching and retrieving images from a large database of digital images. So effective and fast retrieval system becomes important and the need for efficient content-based image retrieval has increased tremendously. The benefits emanating from the application of content-based approaches to medical image retrieval range from clinical decision support to medical education and research. In this paper, we propose an unsupervised approach for efficient content-based medical image retrieval that utilizes similarity measures, decomposing the images into 3 level using biorthogonal spline wavelet transform and then estimating the first two wavelet moments and placed in a feature vector. The spline wavelets based texture features, mean and standard deviation of the magnitudes of the subband coefficients in the wavelet frame decomposition are proposed for image retrieval. When given a query image, its feature vectors are similarly extracted and matched with those in the database. If the distance between the query image features and feature vector available in the database is small enough, the corresponding image in the database is considered a match to the query . The retrieval results are then ranked according to a similarity index and a group of similar target images is usually presented to the users.. It is shown that the proposed scheme can be effectively applied for medical image retrieval from large database, which can be further extended by knowledge representation methodologies.