UMLS-based automatic image indexing.
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.
Sneiderman
C
C
National Library of Medicine, NIH, DHHS, Bethesda, MD, USA.
Sneiderman
Charles Alan
CA
Demner-Fushman
D
D
Demner-Fushman
Dina
D
Fung
K W
KW
Fung
Kin Wah
KW
Bray
B
B
Bray
Bruce
B
D001185:Artificial Intelligence; D003628:Database Management Systems; D004282:Documentation / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D008396:Maryland; D009323:Natural Language Processing; D010363:Pattern Recognition, Automated / Q000379:methods*; D011873:Radiology Information Systems; D009626:Terminology as Topic; D017432:Unified Medical Language System