Synopsis
The IBIV activity supports the development of novel approaches to the analysis of biological research images through the innovative "Ideas Lab" project development and review process. The analysis and visual representation of complex biological images present daunting challenges across all scales of investigation, from multispectral analysis of foliage or algal bloom patterns in satellite images, to automated specimen classification, and tomographic reconstructions in structural biology. Analysis of biological image data is complicated by a host of factors, including: complicated signal to noise profiles; variable feature size, density, scale, and perspective in images; experiment-specific metadata considerations; and reliance on subjective classification criteria. Advances in biological image analyses have the potential to facilitate the automation of analytic processes, improve synthetic approaches to the analysis of large or heterogeneous data collections, and permit higher-order dimensional analyses of complex research models. The goal of this activity is to identify opportunities for investment to advance the state-of-the-art in biological image analysis, data visualization, archiving, and dissemination. Participants selected through an open application process will engage in an intensive five-day residential workshop to generate project ideas through an innovative, real-time review process. Members of the biological research community, computational theorists and engineers, mathematicians, imaging specialists from other fields, educators involved in training the next generation of researchers, and a range of other specialists (artists, illustrators, etc.) are all strongly encouraged to participate.
Program contacts
Name | Phone | Organization | |
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Kamal Shukla
|
kshukla@nsf.gov | 703 292-7131 |