Improving MRI Scans with Smart Technology
TR&D 1: Reimagining the Future of Scanning: Intelligent Image Acquisition, Reconstruction and Analysis
['FUNDING_OTHER'] · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · NIH-11179246
This project aims to make MRI scans simpler, faster, and more informative for patients by using advanced imaging techniques and artificial intelligence.
Quick facts
| Phase | ['FUNDING_OTHER'] |
|---|---|
| Study type | Nih_funding |
| Sex | All |
| Sponsor | NEW YORK UNIVERSITY SCHOOL OF MEDICINE (nih funded) |
| Locations | 1 site (NEW YORK, UNITED STATES) |
| Trial ID | NIH-11179246 on ClinicalTrials.gov |
What this research studies
We are working to transform how MRI scans are done, moving away from complicated and time-consuming procedures. Our goal is to create easy-to-use scanning methods that provide clear, detailed information about specific diseases. By combining expertise in scan design, advanced reconstruction, and machine learning, we can make MRI more intelligent and precise. This will allow for more efficient and effective imaging, including new applications like low-field and diffusion imaging.
Who could benefit from this research
Good fit: This research aims to improve MRI technology for anyone who might need an MRI scan for diagnosis or monitoring of a health condition.
Not a fit: Patients who do not require advanced medical imaging like MRI scans would not directly benefit from this specific technology development.
Why it matters
Potential benefit: If successful, this work could lead to quicker, more comfortable, and more accurate MRI scans, helping doctors better understand and diagnose various health conditions.
How similar studies have performed: Investigators have made substantial progress and significant contributions in this area over previous funding periods, building on established foundations.
Where this research is happening
NEW YORK, UNITED STATES
- NEW YORK UNIVERSITY SCHOOL OF MEDICINE — NEW YORK, UNITED STATES (ACTIVE)
Researchers
- Principal investigator: FENG, LI — NEW YORK UNIVERSITY SCHOOL OF MEDICINE
- Study coordinator: FENG, LI
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 below.