A CBIR System for Human Brain Magnetic Resonance Image Indexing

Abstract

Content-based image retrieval (CBIR) is becoming an important field with the advance of multimedia and imaging technology everincreasingly. It makes use of image features, such as color, shape and texture, to index images with minimal human intervention. Among many retrieval features associated with CBIR, texture retrieval is one of the most powerful. Contentbased image retrieval can also be utilized to locate medical images in large databases. In this research, we introduce a content-based approach to medical image retrieval. A case study, which describes the methodology of a CBIR system for retrieving digital human brain MRI database based on textural features retrieval, is then presented. This research intends to disseminate the knowledge of the CBIR approach to the applications of medical image management and to discrimination between the normal and abnormal medical images based on features. The main indices are finding Normal, Abnormal and clustering the abnormal images to detect two certain abnormalities: Multiple Sclerosis and Tumoral images to classify the database. A classification with a success of 95% has been obtained by the proposed method. This result indicates that the proposed method is robust and effective compared with other recently works.