The Open-i project aims to provide next generation information retrieval services for biomedical articles from the full text collections such as PubMed Central. It is unique in its ability to index both the text and images in the articles. The article retrieval is powered by Essie (the search engine that supports ClinicalTrials.gov).
Open-i lets users retrieve not only the MEDLINE citation information, but also the outcome statements in the article and the most relevant figure from it. Further, it is possible to use the figure as a query component to find other relevant images or other visually similar images. Future stages aim to provide image region-of-interest (ROI) based querying. The initial number of images is projected to be around 600,000 and will scale to millions. The extensive image analysis and indexing and deep text analysis and indexing require distributed computing. At the request of the Board of Scientific Counselors, we intend to make the image computation services available as a NLM service.
Vist our Frequently Asked Questions page for more information and help.
Web Interface: https://openi.nlm.nih.gov/
Batch Query Service: http://openi.nlm.nih.gov/batchindex.php