Improving live fluorescence imaging for better cellular observation
Official title: TR&D3
Funded at University of Michigan at Ann Arbor · NIH-11094976 · Data updated 2026-11-12
This study is working on improving live imaging techniques to help scientists see tiny details of cell behavior more clearly, which is especially important for understanding biological processes in small settings like microendoscopy.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Michigan at Ann Arbor NIH-funded |
| Lab location | 1 site (Ann Arbor, United States) |
| Project start | May 16, 2025 |
| Project end | April 30, 2030 |
| Funding year | 2025 |
| Award (this year) | $280,424 |
| NIH project number | 1P41EB035084-01A1 |
| Project ID | NIH-11094976 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals undergoing procedures that require detailed cellular imaging, such as those with specific cancers or other conditions affecting cellular behavior.
✕Less likely to help
Patients who do not require advanced imaging techniques or those with conditions that do not involve cellular-level analysis may not benefit from this research.
What this research studies
This research focuses on enhancing live fluorescence imaging techniques to capture subtle cellular behaviors more effectively. By developing advanced machine-learning models, the project aims to reduce noise and improve image quality, even at higher frame rates. This is crucial for accurately interpreting biological processes in real-time, especially in small-scale environments like microendoscopy. The approach addresses challenges such as motion artifacts and uneven intensity distributions that can compromise image clarity.
Why it matters
Potential benefit: If successful, this research could lead to more accurate and detailed observations of cellular processes, improving diagnostics and treatment strategies.
How similar studies have gone: Other research in the field of biomedical imaging has shown promising results with machine-learning approaches, indicating a strong potential for success in this novel application.
Where this research is happening
-
University of Michigan at Ann Arbor
Ann Arbor, United States Active
Researchers
- Principal investigator: Cai, Dawen — University of Michigan at Ann Arbor
- Study coordinator: Cai, Dawen
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.