UMLS-based automatic image indexing.
Charles Sneiderman, Charles Alan Sneiderman, D Demner-Fushman, Dina Demner-Fushman, K W Fung, Kin Wah Fung, B Bray, Bruce Bray
Abstract
Charles Sneiderman, Charles Alan Sneiderman, D Demner-Fushman, Dina Demner-Fushman, K W Fung, Kin Wah Fung, B Bray, Bruce Bray
Abstract
To date, most accurate image retrieval techniques rely on textual descriptions of images. Our goal is to automatically generate indexing terms for an image extracted from a biomedical article by identifying Unified Medical Language System (UMLS) concepts in image caption and its discussion in the text. In a pilot evaluation of the suggested image indexing method by five physicians, a third of the automatically identified index terms were found suitable for indexing.
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To date, most accurate image retrieval techniques rely on textual descriptions of images. Our goal is to automatically generate indexing terms for an image extracted from a biomedical article by identifying Unified Medical Language System (UMLS) concepts in image caption and its discussion in the text. In a pilot evaluation of the suggested image indexing method by five physicians, a third of the automatically identified index terms were found suitable for indexing.
Key concepts: Search engine indexing, Unified Medical Language System, Computer science, Information retrieval, Image retrieval, Index (typography), Image (mathematics), Automatic indexing