Improving brain MRI imaging using advanced learning techniques
Official title: Robust and Efficient Learning of High-Resolution Brain MRI Reconstruction from Small Referenceless Data
Funded at University of Minnesota · NIH-11043349 · Data updated 2026-11-12
This study is working on using advanced technology to make brain scans faster and clearer, which could help doctors diagnose and treat brain-related conditions more accurately and quickly for patients like you.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Minnesota NIH-funded |
| Lab location | 1 site (Minneapolis, United States) |
| Project start | March 15, 2023 |
| Project end | February 28, 2027 |
| Funding year | 2025 |
| Award (this year) | $497,944 |
| NIH project number | 5R01EB032830-03 |
| Project ID | NIH-11043349 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include individuals experiencing neuropsychiatric disorders who require advanced brain imaging for diagnosis or treatment.
✕Less likely to help
Patients with conditions that do not require MRI imaging or those who are not affected by neuropsychiatric disorders may not benefit from this research.
What this research studies
This research focuses on enhancing the quality and speed of brain MRI imaging by developing advanced deep learning methods. It aims to create high-resolution brain scans without the need for extensive reference data, which is a common limitation in current MRI techniques. By utilizing artificial intelligence, the project seeks to improve the understanding of neuropsychiatric disorders through better brain imaging. Patients may benefit from faster and more accurate diagnoses and treatment plans based on improved imaging technology.
Why it matters
Potential benefit: If successful, this research could lead to more precise brain imaging, enabling better diagnosis and treatment of neuropsychiatric disorders.
How similar studies have gone: Previous research has shown promise in using deep learning for MRI reconstruction, indicating that this approach could lead to significant advancements in brain imaging.
Where this research is happening
-
University of Minnesota
Minneapolis, United States Active
Researchers
- Principal investigator: Akcakaya, Mehmet — University of Minnesota
- Study coordinator: Akcakaya, Mehmet
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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.