Count-aware modeling for counting-based spectral unmixing in tissue imaging
Official title: Count-Aware Modeling Approaches for Spectral Unmixing in Multispectral Fluorescence Imaging
Funded at State University of New York at Albany · NIH-11442149 · Data updated 2026-11-12
A small NIH grant aims to improve how we separate multiple molecular signals in tissue images by using models that respect the way photons are counted, helping researchers get clearer results from fluorescent images.
Quick facts
| Grant type | R03 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | State University of New York at Albany NIH-funded |
| Lab location | 1 site (Albany, United States) |
| Project start | August 15, 2026 |
| Project end | July 31, 2028 |
| Funding year | 2026 |
| Award (this year) | $72,799 |
| NIH project number | 1R03EB040036-01 |
| Project ID | NIH-11442149 on NIH RePORTER |
Who could benefit from this research
✓Could help
Not applicable in this basic methods grant.
✕Less likely to help
Patients are not directly involved in this non-patient-facing methodological project.
What this research studies
This project focuses on multispectral fluorescence imaging, where many targets are measured at once in tissue samples. It will develop a count-based, statistically principled approach to spectral unmixing that matches photon-counting physics rather than assuming smooth, Gaussian noise. The team will create a unified likelihood-based framework with structured regularization and test it on both simulated and real datasets. They will compare the new method to current best practices to show improvements in accuracy, localization, and reproducibility, especially in low-photon situations. The goal is to provide a computationally efficient tool that makes spatial biology measurements more reliable across experiments and sessions.
Why it matters
Potential benefit: If successful, this could lead to more accurate and reproducible measurements of multiple molecular targets in tissue, enhancing biomedical research and potential clinical insights.
How similar studies have gone: Preliminary work and benchmarking in count-based analysis have shown promise, but this project aims to provide a more unified and robust framework.
Where this research is happening
-
State University of New York at Albany
Albany, United States Active
Researchers
- Principal investigator: Feng, Yunlong — State University of New York at Albany
- Study coordinator: Feng, Yunlong
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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.