Evaluation of automatically assigned MeSH terms for retrieval of medical images

Abstract

This paper presents the results of the State University of New York at Buffalo (UB) team in collaboration with the National Library of Medicine (NLM) in the 2007 ImageCLEFmed task. We use a system that combines visual features (using a CBIR System) and text retrieval. We used the Medical Text Indexer (MTI) developed by NLM to automatically assign MeSH terms and UMLS concepts to the English free text annotations of the images. We also used an equivalent system called MAIF that automatically assigns MeSH and UMLS concepts to French free text. Our results indicate that the use of automatically assigned UMLS concepts improves retrieval performance significantly. We also identified specific aspects of the system that could be improved in the future, such as the method used to perform the automatic translation of medical terms and the addition of image classification to process queries targeted to a specific image modality. © 2008 Springer-Verlag Berlin Heidelberg.