Text and Content-based Approaches to Image Modality Classification and Retrieval for the ImageCLEF 2011 Medical Retrieval Track

This article describes the participation of the Communications Engineering Branch (CEB), a division of the Lister Hill National Center for Biomedical Communications, in the ImageCLEF 2011 medical retrieval track. Our methods encompass a variety of techniques relating to textand content-based image retrieval. Our textual approaches primarily utilize the Unified Medical Language System (UMLS) synonymy to identify concepts in topic descriptions and image-related text, and our visual approaches utilize similarity metrics based on computed “visual concepts” and low-level image features. We also explore mixed approaches that utilize a combination of textual and visual features. In this article we present an overview of the application of our methods to the modality classification, ad-hoc image retrieval, and case-based image retrieval tasks, and we describe our submitted runs and results.