Content-based image retrieval in medical domains: An overview of methods, issues and systems

Abstract

Content-based image retrieval (CBIR) is one of the most interesting research areas of computer vision in recent years. CBIR uses feature comparison to search, browse, and retrieve images from large databases. It is considered as the main research topic in medical fields because of the daily increase in the number of recorded medical images. CBIR can help physicians diagnose various types of diseases as well as medical references, teaching purposes , training and research. This paper introduces the main concepts, stages, and methods of CBIR systems; explores the main types of features that can be extracted from images; and identifies the techniques to evaluate the systems. It also reviews and evaluates the advantages and disadvantages of several existing commercial and academic content-based medical image retrieval systems. Finally, the paper introduces suggestions for the future of medical domains to solve the discussed disadvantages. It proposes the technique of automatic medical image annotation/classification to enhance the accuracy of CBIR systems.