Radiographic Images Data Model for Content-based Retrieval Lilac

With the advance of multimedia technologies in general and diagnostic images technologies specifically, the number of radiographic images is constantly escalating in the biomedical field. This field demands sophisticated systems for management and effective search and retrieval of the radiographic images produced. This paper presents a semantic content-based radiographic image retrieval system that focuses on the semantic content of radiographic image documents to facilitate semantic-based radiographic image indexing and a retrieval system suitable for the radiographic image-on-demand style applications. The paper addresses a model developed for describing the semantic content of a radiographic image document and providing information about this content. It develops a sophisticated semantic radiographic image model that expresses the underlying semantic structure of radiographic images and retrieves content from different levels of details. The proposed semantic model is an extension of the traditional conceptual model which would be applied to the radiographic image domain. The proposed model would divide a radiographic image document, based on its semantic content, and would be converted into a logical structure or a semantic structure. The logical structure represents the overall organization of information. The semantic structure, which is bound to logical structure, is composed of semantic objects with interrelationships in the various spaces in the radiographic image.