Abstract
This paper describes a method for medical images annotation based on the SURF descriptor and the SVM classifier. For the features extraction a Fast-Hessian detector was used. The feature matching was performed with a SVM with a quadratic kernel. The testing of the developed system was performed using a subset of the IRMA radiographic images. The results provided with the SURF descriptor are compared with the ones obtained using the SIFT descriptor with SVM classification. Applying the SURF descriptor resulted in improved classification of lung images with an accuracy over 96%. The research shows that the SURF is a potentially strong tool to be applied in the field of medical image annotation. Together with the SVM classification it may construct an efficient system for automatic medical image retrieval and annotation.
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