Abstract collage of science-related imagery

Innovations in Biological Imaging and Visualization (IBIV)

Status: Archived

Archived funding opportunity

This document has been archived.

Important information about NSF’s implementation of the revised 2 CFR

NSF Financial Assistance awards (grants and cooperative agreements) made on or after October 1, 2024, will be subject to the applicable set of award conditions, dated October 1, 2024, available on the NSF website. These terms and conditions are consistent with the revised guidance specified in the OMB Guidance for Federal Financial Assistance published in the Federal Register on April 22, 2024.

Important information for proposers

All proposals must be submitted in accordance with the requirements specified in this funding opportunity and in the NSF Proposal & Award Policies & Procedures Guide (PAPPG) that is in effect for the relevant due date to which the proposal is being submitted. It is the responsibility of the proposer to ensure that the proposal meets these requirements. Submitting a proposal prior to a specified deadline does not negate this requirement.

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

Kamal Shukla
kshukla@nsf.gov 703 292-7131

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