Content-based and metadata retrieval in medical image database
Solomon Atnafu, Richard Chbeir, Lionel Brunie · 2003
The need for systems that can store, represent and provide efficient retrieval facilities for images of particular interest is becoming very high in medicine. In this respect, a lot of work has been done to integrate image data in standard data processing environments. The two different approaches that are used for the representation of images are the meta-data and the content-based approaches. Users in medicine need queries that use both content-based and meta-data representations of images or salient objects. In this paper, we first present a global image data model that supports both meta-data and low-level descriptions of images and their salient objects. This allows us to make multi-criteria image retrieval (context-, semantic- and content-based queries). Then, we present an image data repository model that captures all the data described in the model and permits the integration of heterogeneous operations in a DBMS. In particular, content-based operations (content-based join and selection) in combination with traditional ones can be carried out using our model.