We propose to advance biomedical literature mining by providing new technologies for searching and retrieving biomedical images. The content of these images is a good representation of the research results discussed in scientific articles, and often contains additional facts not explicitly mentioned in the article or image caption. While the inherent structure in biomedical images facilitates automated image content extraction, the extraction process can be made more accurate by concurrent processing of text and images. Text-enhanced image analysis results in richly annotated images, which open up new possibilities for locating images of interest.
The specific aims are to 1) develop methods for extracting structured image content through image processing and analysis, to 2) design methods to boost accuracy of image understanding through concurrent processing of text and images, to 3) devise methods for searching across structured image content, and 4) to develop an image search tool that demonstrates the power of using structured Image content for accessing the biomedical literature.

Public Health Relevance

We propose to advance our ability to search Millions of published research articles by looking into the images within those articles. Our methodology understands the text and layout within images, allowing for very precise image searches. The methodology should have a broad impact on our ability to access the biological and medical literature.

Agency
National Institute of Health (NIH)
Institute
National Library of Medicine (NLM)
Type
Research Project (R01)
Project #
5R01LM009956-03
Application #
8138362
Study Section
Biomedical Library and Informatics Review Committee (BLR)
Program Officer
Ye, Jane
Project Start
2009-09-01
Project End
2014-08-31
Budget Start
2011-09-01
Budget End
2014-08-31
Support Year
3
Fiscal Year
2011
Total Cost
$321,995
Indirect Cost
Name
Yale University
Department
Pathology
Type
Schools of Medicine
DUNS #
043207562
City
New Haven
State
CT
Country
United States
Zip Code
06520
Fodeh, Samah Jamal; Brandt, Cynthia; Luong, Thai Binh et al. (2013) Complementary ensemble clustering of biomedical data. J Biomed Inform 46:436-43
Fodeh, Samah Jamal; Haddad, Ali; Brandt, Cynthia et al. (2012) Enhancing Clustering by Exploiting Complementary Data Modalities in the Medical Domain. IFIP Adv Inf Commun Technol 381:357-367
Kuhn, Tobias; Luong, ThaiBinh; Krauthammer, Michael (2012) Finding and accessing diagrams in biomedical publications. AMIA Annu Symp Proc 2012:468-74
Evans, Perry; Krauthammer, Michael (2011) Exploring the use of social media to measure journal article impact. AMIA Annu Symp Proc 2011:374-81
Xu, Songhua; Krauthammer, Michael (2010) A new pivoting and iterative text detection algorithm for biomedical images. J Biomed Inform 43:924-31