  Content-based image retrieval (CBIR) of medical images in large datasets to
identify similar images when a query image is given can be very useful in
improving the diagnostic decision of the clinical experts and as well in
educational scenarios. In this paper, we used two stage classification and
retrieval approach to retrieve similar images. First, the Gabor filters are
applied to Radon-transformed images to extract features and to train a
multi-class SVM. Then based on the classification results and using an
extracted Gabor barcode, similar images are retrieved. The proposed method was
tested on IRMA dataset which contains more than 14,000 images. Experimental
results show the efficiency of our approach in retrieving similar images
compared to other Gabor-Radon-oriented methods.
