Text- and Content-based Approaches to Image Modality Detection and Retrieval for the ImageCLEF 2010 Medical Retrieval Track
Matthew S. Simpson, Md Mahmudur Rahman, Srinivas Phadnis, Emilia Apostolova, Dina Demner‐Fushman, Sameer Antani, George R. Thoma · 2010
This article describes the participation of the Image and Text Integration (ITI) group from the U.S. National Library of Medicine (NLM) in the ImageCLEF 2010 medical retrieval track. Our methods encompass a variety of techniques relating to document summarization and text- and content-based image retrieval. Our text-based approaches utilize the Unified Medical Language System (UMLS) synonymy to identify concepts in information requests and image-related text in order to retrieve semantically relevant images. Our image content-based approaches utilize similarity metrics based on computed “visual concepts ” and lowlevel image features to identify visually similar images. In this article we present an overview of the application of our methods to the modality detection, ad-hoc image retrieval, and case-based retrieval tasks and describe our submitted runs and results.