Problem statement: Recently, there has been a huge progress in collection of varied image databases in the form of digital. Most of the users found it difficult to search and retrieve required images in large collections. In order to provide an effective and efficient search engine tool, the system has been implemented. In image retrieval system, there is no methodologies have been considered d...

This paper describes our participation in the Medical Image Retrieval task of Image CLEF 2008. Our aim was to evaluate different combination methods for purely textual and visual approaches. Our most interesting conclusion is that combining results provided by both methods using classical combination function allows to obtain higher retrieval accuracy in terms of MAP . MAP values than combinati...

Nowadays, Medical Imaging is emerged well with computer applications. The diagnosis process is fully automated; based on the medical image, cases are reasoned to examine the causes such as Cancer Prediction, Age Estimation, and Injuries and so on. Automatic Image Annotation (AIA) is widely used in Medical field. Generally, the images are the retrieved using CBIR (Content-based Image Retrieval) ...

This paper describes the medical image retrieval and annotation tasks of ImageCLEF 2006. Both tasks are described with respect to goals, databases, topics, results, and techniques. The ImageCLEFmed retrieval task had 12 participating groups (100 runs). Most runs were automatic, with only a few manual or interactive. Purely textual runs were in the majority compared to purely visual runs but mos...

Introduction Problems with traditional methods of image indexing [4] have led to great interest in Content-Based Image Retrieval (CBIR) techniques, which employ automatically derived features such as color, texture, and shape as search criteria [8]. The CBIR problem is a challenging topic of current research [5] and is of growing interest in medical applications such as medical records systems....

The growing repositories of clinical imaging data generate a need for effective image management and access that demands more than simple text-based queries. Content-Based Image Retrieval (CBIR) is an active research field and has drawn attention in recent years. It is a technique to organize and search image archives by their visual content. It is a multi-discipline field that integrates techn...

OBJECTIVES The objective of this article is to provide an overview of current trends in medical multimedia retrieval. This state of the art is then compared with trends and techniques in the Web 2.0 field that addresses several of the problems of current multimedia retrieval and may help in solving them. METHODS The article uses a review of the current literature on medical imaging and medica...

This paper describes the medical image retrieval and medical image annotation tasks of ImageCLEF 2007. Separate sections describe each of the two tasks, with the participation and an evaluation of major findings from the results of each given. A total of 13 groups participated in the medical retrieval task and 10 in the medical annotation task. The medical retrieval task added two new data sets...

The increasing necessity of image retrieval based on content given technique can be used in a number of domains like Data Mining, Academics, Medical, Crime Prevention, Weather forecasting, Remote sensing and Management of Resources. This paper presents the content based image retrieval , using an edge detection called as canny edge detection algorithm in which the image can be viewed as binary ...