Using AI to improve nuclear imaging technology
Official title: AI-accelerated optical simulation for fast timing nuclear imaging
Funded at University of California at Davis · NIH-10906979 · Data updated 2026-11-12
This study is working on making nuclear imaging techniques like PET and SPECT better by using AI to help create clearer and more accurate images, which could lead to improved diagnoses for patients.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of California at Davis NIH-funded |
| Lab location | 1 site (Davis, United States) |
| Project start | August 15, 2023 |
| Project end | July 31, 2027 |
| Funding year | 2024 |
| Award (this year) | $603,056 |
| NIH project number | 5R01EB034475-02 |
| Project ID | NIH-10906979 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are patients undergoing nuclear imaging procedures, particularly those requiring PET or SPECT scans.
✕Less likely to help
Patients who do not require nuclear imaging or those with conditions that do not involve the use of PET or SPECT technology may not benefit from this research.
What this research studies
This research focuses on enhancing the performance of nuclear imaging technologies, specifically positron emission tomography (PET) and single photon emission computed tomography (SPECT). By developing an AI-based optical modeling framework, the project aims to accelerate the simulation of how these imaging systems work, allowing for faster and more accurate image formation. This involves integrating complex physics simulations to better understand the optical mechanisms at play in radiation detectors. The ultimate goal is to improve the spatial resolution and quantification capabilities of these imaging techniques, which could lead to better diagnostic outcomes for patients.
Why it matters
Potential benefit: If successful, this research could lead to more accurate and faster nuclear imaging, improving diagnosis and treatment planning for various medical conditions.
How similar studies have gone: Other research has shown promise in using AI to enhance imaging technologies, indicating that this approach could lead to significant advancements in the field.
Where this research is happening
-
University of California at Davis
Davis, United States Active
Researchers
- Principal investigator: Roncali, Emilie — University of California at Davis
- Study coordinator: Roncali, Emilie
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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.