The rapid expansion and improvement in medical science and technology which generates the amount of image data more and more in its regular activity such as CT-image, X-ray, MRI etc. Due to scalability of image data, it has been increased in size of database and containing millions of images. For the proper management of medical image and requirement of efficient retrieval system for clinical d...

Digital images are now the basis of visual information in medical applications. The advent of radiology which employs imaging for diagnosis generates great amount of images. Automatic retrieval of images based on features like color, shape and texture is termed Content Based Image Retrieval. The increasing dependence of modern medicine on diagnostic techniques such as radiology, computerized to...

One important challenge in modern Content-Based Medical Image Retrieval (CBMIR) approaches is represented by the semantic gap, related to the complexity of the medical knowledge. Among the methods that are able to close this gap in CBMIR, the use of medical thesauri/ontologies has interesting perspectives due to the possibility of accessing on-line updated relevant webservices and to extract re...

Medical images are critical assets for medical diagnosis, research, and teaching. To facilitate automatic indexing and retrieval of large medical image databases, we propose a structured framework for designing and learning vocabularies of meaningful medical terms with associated visual appearance from image samples. These VisMed terms span a new feature space to represent medical image content...

Combining low-level features that represent the content of medical images with high level features that are saved with images would allow the expansion of text queries submitted to Content Based Image Retrieval (CBIR) systems. Expanding these text queries would allow CBIR systems to respond more effectively to specific queries when retrieving medical images. We hypothesized that adding an autom...

Contour trees have been used in geographic information systems (GIS) and medical imaging to display scalar data. Contours are only defined for continuous functions. For an image represented by discrete data, a continuous function is first defined as an interpolation of the data. Then the contour tree is defined on this continuous function. In this paper, we introduce a new concept termed monoto...

In this paper, we present a content-based image retrieval system designed to retrieve mammographies from large medical image databases. The system is developed based on breast density and lesion, according to the categories defined by the American College of Radiology, and is integrated to the database of the Image Retrieval in Medical Applications (IRMA) project, that provides images with clas...