Digital microscope camera and AI support for routine pathology
PathCAM: connecting the digital data pipeline in diagnostic pathology with onboard-camera variable resolution slide imaging
This project builds a low-cost camera and software that captures microscope views and gives pathologists AI-based help when reading patient tissue slides.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Tulane University of Louisiana NIH-funded |
| Lab location | 1 site (New Orleans, United States) |
| Project ID | NIH-11136402 on NIH RePORTER |
What this research studies
If you have a biopsy or tissue sample, this work aims to quietly capture the exact microscope views your pathologist uses, creating digital images without changing routine practice. The team will attach and improve software for cameras already on clinical microscopes so images are made passively as slides are reviewed. Those images will be combined with AI tools to highlight important areas and support pathologists' decisions. The goal is to make digital pathology assistance affordable and available in hospitals that lack expensive whole-slide scanners.
Who could benefit from this research
Good fit: Ideal candidates are patients who are having tissue biopsies or surgical specimens reviewed by pathologists at hospitals or labs that use standard light microscopes without routine whole-slide scanning.
Not a fit: Patients whose care does not involve tissue pathology or who are already at centers routinely using full whole-slide imaging systems may see little direct benefit from this project.
Why it matters
Potential benefit: If successful, this could speed up and improve the accuracy of pathology diagnoses and expand access to AI-powered diagnostic help in more hospitals.
How similar studies have performed: AI tools applied to digitized whole-slide images have shown promising results in research settings, but passively capturing microscope video with onboard cameras and integrating it into routine clinical workflow is a newer, less-tested approach.
Where this research is happening
New Orleans, United States
- Tulane University of Louisiana — New Orleans, United States (Active)
Researchers
- Principal investigator: Brown, Jonathan Quincy — Tulane University of Louisiana
- Study coordinator: Brown, Jonathan Quincy
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.