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The Open-ism (pronounced “open eye”) experimental multimedia search engine retrieves and displays structured MEDLINE citations augmented by image-related text and concepts and linked to images based on image features.
The Open-i project provides novel 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 the LHNCBC-built search engine Essie.
The Open-I biomedical image search engine 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. Future plans include making the image computation services available as a NLM service.