Using machine learning to improve brain artery imaging
Automated Machine Learning-Based Brain Artery Segmentation, Anatomical Prior Labeling, and Feature Extraction on MR Angiography
This study is looking to make it easier and faster to check the health of brain arteries using advanced computer technology, which could help doctors better understand and diagnose conditions related to small blood vessels in the brain and how they affect thinking skills.
Quick facts
| Grant type | R03 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Rochester NIH-funded |
| Lab location | 1 site (Rochester, United States) |
| Project ID | NIH-10759721 on NIH RePORTER |
What this research studies
This research focuses on enhancing the evaluation of brain arteries using advanced machine learning techniques applied to magnetic resonance angiography (MRA). It aims to automate the segmentation of cerebral vessels, which is currently a time-consuming manual process, thereby improving the speed and accuracy of diagnosing cerebrovascular diseases. The study will utilize existing databases to develop a framework that requires minimal training data while extracting important features from the images. Additionally, it will explore the connections between these vessel features and cognitive performance in patients with cerebral small vessel disease.
Who could benefit from this research
Good fit: Ideal candidates for this research include individuals diagnosed with cerebrovascular diseases or those at risk, particularly those with cognitive impairments related to small vessel disease.
Not a fit: Patients without cerebrovascular conditions or those not undergoing imaging studies may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to faster and more accurate diagnoses of cerebrovascular diseases, ultimately improving patient outcomes.
How similar studies have performed: While there have been some machine learning approaches in medical imaging, this specific application of automated segmentation in brain artery imaging is relatively novel.
Where this research is happening
Rochester, United States
- University of Rochester — Rochester, United States (Active)
Researchers
- Principal investigator: Uddin, Md Nasir — University of Rochester
- Study coordinator: Uddin, Md Nasir
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.