CONTENT BASED IMAGE RETRIEVAL FOR MEDICAL IMAGES

Content Based Image Retrieval (CBIR) is one of the outstanding areas in Computer Vision and Image Processing [1]. Content Based Image Retrieval systems retrieve images from that database which are similar to the query image. This is done by actually matching the content of the query image with the images in database. Image database can be hug, containing hundreds of thousands or millions of images. In common case, those only indexed by keywords entered in database systems by human operators. Images Content of an image can be described in terms of color, shape and texture of an image. CBIR in radiology has been a topic of research interest for nearly a decade. Content Based Image Retrieval in medical is one of the prominent areas in Computer Vision and Image Processing. CBIR can be used to locate radiology images in large radiology image databases. The main goal of CBIR in medical is to efficiently retrieve images that are visually similar to a query. In this paper we will focus on CBIR from large medical databases, outline the problems specific to this area, and describe the recent advances in the field. Our goal in this paper is to describe CBIR methods and systems from the perspective of application to medical and to identify approaches developed in nonmedical applications that could be translated to medical.