Healthcare / Radiology
AI-Powered X-Ray Patient Positioning System
An intelligent Raspberry Pi device that automatically detects and tracks patient body parts inside an X-ray machine, then controls motors to align the collimator in real time — replacing manual calibration with AI precision.
$0
Cloud dependency
+40%
Positioning accuracy
3x
Faster calibration
The Challenge
Radiology technicians were manually positioning X-ray collimators for every patient — a repetitive, error-prone process that slowed imaging workflows. Misalignment meant retakes, higher radiation exposure, and wasted time. The client needed an automated solution that could run standalone on low-cost hardware.
Our Approach
We built a compact embedded system on a Raspberry Pi that uses a camera module to detect patient anatomy in real time. An AI object detection model identifies body parts, while a control loop drives stepper motors to align the collimator. The entire stack runs on-device — no cloud, no latency.
The Results
Real-time body part detection with 95%+ confidence
Automated motor-driven collimator alignment
Fully standalone — no internet required
Reduced technician workload by 60%
Compact, cost-effective hardware footprint
System Architecture
Camera Module
→
AI Detection Engine
→
Tracking Algorithm
→
Collimator
→
Motor Controller
Embedded Linux
Python
Motor Control
Sensor Fusion
Computer Vision
Object Detection
Raspberry Pi