Content Based Image Retrieval Techniques for Retrieval of Medical Images From Large Medical Datasets – A Survey

Abstract

In this computing era, data are represented as images that are to be processed for retrieval. Need for high accuracy in retrieval made this area more challenging. Content Based Image Retrieval system uses features of query image with that of an existing database image set for retrieval using precision and recall ratio. Features of images include color, shape, texture, etc. Techniques for retrieval include histogram, wavelength transformation, statistical methods, Euclidean distance, etc. Color feature though forms the fundamental image feature for retrieval techniques, other features are also considered to be more important and necessary as they play vital role in retrieval process. Many programs and tools have been developed to formulate and execute queries. CBIR researchers need to improve precision rate (accuracy), that lead to variation of search ranges and search object increment. This in turn brought about the combination of two or more features for efficient retrieval. Together with features, today's research is highly concentrated on image set with large varied databases, documents of differing sorts and with varying characteristics that have high social implications. The image set can be motion or motionless. Earlier research concentrated on motionless images in CBIR while motion images are also considered in recent years. This paper presents the literature survey on recent medical image retrieval techniques.