Advancing Literature Mining through Image Processing and Analysis

描述(由申请人提供)：我们建议通过提供搜索和检索生物医学图像的新技术来推进生物医学文献挖掘。这些图像的内容很好地代表了科学文章中讨论的研究结果，并且经常包含文章或图像标题中没有明确提到的附加事实。虽然生物医学图像的固有结构有助于自动提取图像内容，但通过同时处理文本和图像，可以使提取过程更加准确。文本增强的图像分析产生了带丰富注释的图像，这为定位感兴趣的图像开辟了新的可能性。其具体目标是1)开发通过图像处理和分析提取结构化图像内容的方法，2)设计通过文本和图像的并行处理来提高图像理解的准确性的方法，3)设计跨结构化图像内容进行搜索的方法，以及4)开发一种图像搜索工具，该工具展示了使用结构化图像内容访问生物医学文献的能力。

DESCRIPTION (provided by applicant): 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.