Image retrieval is an important research field which has received great attention in the last decades. In this paper, we present an approach for the image retrieval based on the combination of text-based and content-based features. For text-based features, keywords and for content-based features, color and texture features have been used. Query in this system contains some keywords and an input...

In the medical field, images, and especially digital images, are produced in ever increasing quantities and used for diagnostics and therapy. Imaging has occupied a huge role in the management of patients, whether hospitalized or not. This gave birth of the annotation of medical image process. The annotation is intended to image analysis and solve the problem of semantic gap. Physicians and rad...

Many clinical tasks depend upon the proper interpretation of medical images and will benefit from access and reference to similar, relevant images. In this paper, we present CBIR approaches to two clinical tasks and discuss their specific challenges. The first CBIR system retrieves anatomical regions in Computed Tomography (CT) studies of the chest and abdomen. The system can be used to provide...

In this paper, we provide an overview of the first workshop on Medical Content–Based Retrieval for Clinical Decision Support (MCBR– CDS), which was held in conjunction with the Medical Image Computing and Computer Assisted Intervention (MICCAI) conference in 2009 in London, UK. The goal of the workshop was to bring together researchers from diverse communities including medical image analyses, ...

The goal of the ImageCLEF medical image retrieval task (ImageCLEFmed) has been to improve understanding and system capability in search for medical images. This has been done by developing a test collection that allows system-oriented evaluation of medical image retrieval systems. From 2005-2007, test collections were developed and used for ImageCLEFmed. This paper describes our recent work con...

Content-based image retrieval (CBIR) is an application of computer vision techniques for the image retrieval problem, specifically the search for specific medical images in large databases. In this work the X-ray images are taken from the medical database includes skull, spine, chest and leg x-ray images. The X-ray images are taken in the .jpeg format. In this project, a complete solution for s...

Computational social scientists often harness the Web as a “societal observatory” where data about human social behavior is collected. This data enables novel investigations of psychological, anthropological and sociological research questions. However, in the absence of demographic information, such as gender, many relevant research questions cannot be addressed. To tackle this problem, resear...

Content Based Image Retrieval (CBIR) is an evolving topic under image processing. Retrieval on medical images plays a vital role in saving mankind. Medical Content Based Image Retrieval (MCBIR) does not stop its work in displaying similar images; it also goes one step further for diagnosis to decide the method of therapy by comparing the query image and database image. Hence we believe that, ou...