Improving brain blood flow diagnosis using advanced imaging and machine learning.
Enhanced Clinical Diagnosis through Imaging and Modeling: A Machine Learning Data Fusion Framework
This study is looking to improve how doctors understand blood flow in the brain by using smart computer techniques alongside medical images, which could help both healthy people and stroke survivors get better and faster diagnoses.
Quick facts
| Grant type | R21 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Pittsburgh at Pittsburgh NIH-funded |
| Lab location | 1 site (Pittsburgh, United States) |
| Project ID | NIH-10676278 on NIH RePORTER |
What this research studies
This research aims to enhance the accuracy of brain blood flow diagnosis by integrating machine learning techniques with clinical imaging data. By combining computational modeling with real clinical measurements, the project seeks to provide more detailed and informative predictions about brain hemodynamics. The approach involves using a probabilistic data-fusion framework that can operate in real-time, potentially replacing existing models that are too costly to compute. The focus will be on applying this framework to both healthy individuals and those who have suffered a stroke, aiming for significant improvements in clinical workflows.
Who could benefit from this research
Good fit: Ideal candidates for this research include individuals with cerebrovascular conditions, such as stroke patients, as well as healthy volunteers for comparative analysis.
Not a fit: Patients with conditions unrelated to brain blood flow or those who do not undergo imaging procedures may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to more accurate and timely diagnoses of brain blood flow issues, improving patient outcomes.
How similar studies have performed: Other research has shown promise in using machine learning for medical imaging, indicating that this approach could lead to significant advancements in clinical practice.
Where this research is happening
Pittsburgh, United States
- University of Pittsburgh at Pittsburgh — Pittsburgh, United States (Active)
Researchers
- Principal investigator: Babaee, Hessam — University of Pittsburgh at Pittsburgh
- Study coordinator: Babaee, Hessam
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.