SPIRS: a framework for content-based image retrieval from large biomedical databases.
With the increasing use of medical images in clinical medicine, disease research, and education, the need for methods that effectively archive, query, and retrieve these images by their content is underscored. This paper presents the implementation of a Web-based retrieval system called SPIRS (Spine Pathology & Image Retrieval System) at the U. S. National Library of Medicine that demonstrates recent developments in shape representation and retrieval from a large dataset of 17,000 digitized x-ray images of the spine and associated text records. Users can search these images by providing a sketch of the vertebral outline or selecting an example vertebral image and some relevant text parameters. Pertinent pathology on the image/sketch can be annotated and weighted to indicate importance. This hybrid text-image query yields images containing similar vertebrae along with relevant fields from associated text records, which allows users to examine the pathologies of vertebral abnormalities. Initial experiments with SPIRS have demonstrated the potential for this system, particularly on a large dataset of clinical images.
Hsu
William
W
Medical Imaging Informatics Group, University of California, Los Angeles, CA 90024, USA. willhsu@mii.ucla.edu
Long
L Rodney
LR
Antani
Sameer
S
D000043:Abstracting and Indexing; D000465:Algorithms; D019992:Databases as Topic; D003952:Diagnostic Imaging; D016247:Information Storage and Retrieval; D020407:Internet; D011857:Radiographic Image Interpretation, Computer-Assisted; D011873:Radiology Information Systems; D013131:Spine / Q000000981:diagnostic imaging