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Smart cloud system with image processing server in diagnosing brain diseases dedicated for hospitals with limited
Fahmi Fahmi1, Tigor H Nasution1, Anggreiny Anggreiny2
1Department of Electrical Engineering, University of Sumatera Utara (USU), Medan, Indonesia.
Summary
A smart cloud system aids brain tumor diagnosis for hospitals with limited resources. It uses cloud-based image processing for real-time analysis, providing tumor size and location data.
Area of Science:
- Medical imaging
- Cloud computing
- Neurology
Background:
- Medical imaging use for brain disease diagnosis is increasing.
- Large data size and complex image processing pose challenges.
- High-end hardware and software are required, limiting access for smaller hospitals.
Purpose of the Study:
- To develop a smart cloud system for brain disease diagnosis.
- To assist hospitals with limited infrastructure.
- To enable real-time, automated diagnosis using medical images.
Main Methods:
- Expertise of neurologists was integrated into a cloud server.
- Real-time automatic diagnosis was performed using image processing techniques.
- A web service and ITK library were utilized for image analysis.
- A specialized image compression technique was developed.
Main Results:
- The system accurately measured tumor area (average 19.91 ± 2.38 cm²) and location.
- Average response time was 7.0 ± 0.3 seconds.
- System performance decreased with multiple simultaneous users (14s for 5 clients, 27s for 10 clients).
Conclusions:
- The smart cloud system successfully processes and analyzes medical images for brain tumor diagnosis.
- It provides a viable solution for healthcare facilities with limited infrastructure.
- The system demonstrates the potential of cloud-based solutions in medical diagnostics.
