RSS
 Print this
 E-mail this
|
The Communications Engineering Branch (CEB) is part of the Lister Hill National Center for Biomedical Communications, an R&D division of the U.S. National Library of Medicine. Our mission is to conduct research and development directed toward mission-critical tasks at NLM and NIH, such as cancer research, document delivery, digital preservation, and automated ways of building resources such as MEDLINE®. All software products developed by our researchers are freely available.
A major focus at CEB is image engineering, both for biomedical as well as document images. This includes research in image processing, compression and enhancement. Other research is targeted toward text and data mining. Our work in these areas employs machine learning and natural language processing techniques. Scientific papers by staff appear under publications.
Show All
Biomedical Imaging
Recent Publications
Antani S: The Role of Image Modality and Visual Characteristics In Archiving Biomedical Images. Apr. 2013.
Bryant B: Fast GPU-based Segmentation of H&E Stained Squamous Epithelium From Multi-gigapixel Tiled Virtual Slides. Feb. 2013.
Kamalakannan S: Customized Hybrid Level Sets For Automatic Lung Segmentation In Chest X-ray Images. Feb. 2013.
Kamalakannan S: Integrating Shape Into an Interactive Segmentation Framework. Feb. 2013.
You D: Text- and Content-based Biomedical Image Modality Classification. Feb. 2013.
ReUnite (tm) for Android released
ReUnite (tm) app for post-disaster family reunification was released for Android devices. It is available at the link below.
CEB Staff Honors -- October 2011
Dr Dina Demner-Fushman was elected to the membership of the American College of Medical Informatics for major contributions to research in natural language processing and information management for biomedicine. Dr Daniel Le received the Regents Award for Scholarship or Technical Achievement in recognition for leading the development of the Publisher Data Review System to automatically extract bibliographic data from full-text articles, frequently missing in citations sent to NLM by publishers.
CEB Paper #2 in IEEE TITB
Dr. Rahman's paper, "A Learning-Based Similarity Fusion and Filtering Approach for Biomedical Image Retrieval Using SVM Classification and Relevance Feedback," was the second most viewed article in IEEE Transactions on Information Technology in Biomedicine in July 2011.
National Institutes of Health (NIH)
U.S. Dept. of Health