VescuEye
Team
- E/20/248, T.L.B Mapagedara, email
- E/20/158, J.G.C Jananga, email
- E/20/453, R.J Yogesh, email
- E/20/300, H.A.M.T Prasadinie, email
Supervisor
- Dr. Isuru Nawinne, email
Introduction Video
Hardware Setup
Image Enhance Process
Table of Contents
- Introduction
- Solution Architecture
- Hardware & Software Designs
- Web & Mobile Applications
- Testing
- Detailed Budget
- Conclusion
- Links
Introduction
VascuEye is a medical imaging system that utilizes near-infrared (NIR) technology to detect arteries and assist in both preoperative planning and post-surgical inspection for oral and facial surgeries. By providing real-time visualization of blood vessels, the system helps surgeons avoid accidental arterial damage and simplifies post-surgical monitoring to detect complications like hematomas or poor blood circulation.
Applications & Benefits
- ✅ Enhanced Surgical Accuracy – Helps avoid arterial damage during procedures.
- ✅ Faster & Easier Post-Surgical Inspection – Reduces reliance on manual monitoring.
- ✅ Real-Time Blood Flow Monitoring – Detects complications early.
- ✅ Portable & Affordable Solution – More accessible than high-end imaging devices.
- ✅ Remote Monitoring Support – Enables telemedicine and second opinions.
Solution Architecture
Hardware and Software Designs
Hardware Components
- Raspberry Pi NoIR V2 Camera – Captures near-infrared images of veins.
- MLX90614 Temperature Sensor – Measures skin surface temperature for patient monitoring.
- IR LEDs (850nm, 940nm) – Enhances vein visibility under NIR light.
- Raspberry Pi 3 Model B – Processes the images and runs the web interface.
- LCD Display – Displays real-time feedback.
- Power Bank – Ensures portable operation.
Software Stack
- Backend: Node.js, Express.js, MongoDB
- Frontend: React, Tailwind CSS
- Mobile App: React Native, Expo
- Image Processing: OpenCV, TensorFlow
Web & Mobile Applications
Web Application
- Built with React and Node.js to provide a user-friendly dashboard for doctors.
- User Roles:
- Doctors can monitor patients and view real-time vein images.
- Hospitals can register doctors and assign patients.
- Patients can access their reports and track their recovery.
- Authentication & Security: JWT-based authentication ensures secure access.
- Data Storage: MongoDB is used for storing patient data and image records.
Mobile Application
- Developed using React Native & Expo for cross-platform support.
- Features:
- Real-time blood flow monitoring via mobile.
- Secure login and role-based access.
- Push notifications for critical alerts.
- Integration with the web dashboard for patient tracking.
- Notifications: Firebase Cloud Messaging (FCM) for mobile alerts.
Testing
Comprehensive testing on both hardware and software components:
- Hardware Testing: Accuracy of temperature readings, infrared imaging performance.
- Software Testing: Web & mobile application functionality, security, and performance.
- Usability Testing: Evaluation with medical professionals for feedback.
Detailed Budget
All items and costs
| Item | Quantity | Unit Cost | Total |
|---|---|---|---|
| Temperature Sensor (MLX90614) | 1 | Rs. 4500.00 | Rs. 4500.00 |
| Raspberry Pi 3 Model B | 1 | Rs. 20400.00 | Rs. 20400.00 |
| Raspberry Pi NoIR Camera Sony IMX219 | 1 | Rs. 7200.00 | Rs. 7200.00 |
| IR LEDs (850nm) | 10 | Rs. 200.00 | Rs. 2000.00 |
| IR LEDs (940nm) | 10 | Rs. 200.00 | Rs. 2000.00 |
| 5 Inch LCD Display | 1 | Rs. 10500.00 | Rs. 10500.00 |
| Wires and Other Electronic Components | - | Rs. 1000.00 | Rs. 1000.00 |
| Power Bank (10000 mAh) | 1 | Rs. 2500.00 | Rs. 2500.00 |
| Total Price | Rs. 47400.00 |
Conclusion
VascuEye successfully integrates hardware-based vein visualization with web and mobile applications, enabling efficient real-time monitoring of blood circulation. Future improvements may include:
- AI-based vein detection and segmentation.
- Enhanced thermal imaging for deeper tissue analysis.
- Cloud-based patient data storage for seamless access.