Despite over a decade of research into content-based image retrieval (CBIR), the task of finding a desired image in a large collection remains problematic. Even in application areas where there is a clear need for effective image retrieval, such as medical diagnosis and trademark registration, current technology fails to meet user needs. Much existing research has concentrated on retrieval tech...

The Medical image database is growing day by day. There are various categories of medical images [1] such as CT scan, XRay, Ultrasound, Pathology, MRI, Microscopy, etc. Physicians compare previous and current medical images associated with patients to provide right treatment. Medical Imaging is playing a leading role in modern diagnosis. Efficient image retrieval tools are needed to retrieve th...

One of the main challenges in content-based image retrieval still remains to bridge the gap between low-level features and semantic information. In this paper, we present our first results concerning a medical image retrieval approach using a semantic medical image and report indexing within a fusion framework, based on the Unified Medical Language System (UMLS) metathesaurus. We propose a stru...

The purpose of this paper is to describe solution to the problem of designing a Content Based Image Retrieval (CBIR) system. CBIR has become an active and fast-advancing research area in image retrieval in the last decade. With the rapid development of computer technology, the amount of digital imagery data is rapidly increasing. There is an inevitable need for efficient methods that can help i...

The Medical image database is growing day by day [1]. Most of the medical images are stored in DICOM (Digital Imaging and Communications in Medicine) format. There are various categories of medical images such as CT scan, XRay, Ultrasound, Pathology, MRI, Microscopy, etc [2]. Physicians compare previous and current medical images associated patients to provide right treatment. Medical Imaging i...

With the development of the internet, medical images are now available in large numbers in online repositories, and there exists the need to retrieval the medical images in the content-based ways through automatically extracting visual information of the medical images. Since a single feature extracted from images just characterizes certain aspect of image content, multiple features are necessa...

Recent research has suggested that there is no general similarity measure which can be applied parameter free on arbitrary databases. In contrast the optimal combination of similarity measures and parameters must be identified for each new image repository. This optimization loop is time consuming and depends on the experience of the designer as well as the knowledge of the medical expert. It w...

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. Content-based image retrieval can also be u...