Medical image retrieval by combining low level features and DICOM features

Content based image retrieval aims at searching the image databases using non-textual information which are low level features like color, shape and texture. Medical image databases contain lot of textual or semantic information. This paper presents an approach by combining low level content features and high level semantic features to perform retrieval on medical image databases. The semantic information is extracted from DICOM header which is used to perform the initial search and images are retrieved. This pre-filtering of the images reduces the number of images to be searched. Content-based retrieval is performed only to the pre filtered image database which speeds up the retrieval process. Retrieval is performed by extracting shape and texture features. Experimental result shows that by combining the high level semantics (DICOM features) and low level content features (shape and texture) the retrieval time is reduced and the performance of medical image retrieval is increased.