Healthcare & Compliance
Advancing Prenatal Care & Compliance with AI-Driven Ultrasound Security
In regions where access to safe prenatal imaging is limited, our platform unlocks cost-effective, point-of-care ultrasound while embedding real-time compliance safeguards.
The Challenge: Scaling Safe Ultrasound in Resource-Constrained Settings
- Low Penetration of USG Devices: Traditional cart-based machines are expensive and immobile, limiting rural access.
- Regulatory Complexity: The PC-PNDT Act mandates strict controls, but manual auditing hinders enforcement.
- Risk of Misuse: Unauthorized attempts at fetal-sex determination violate laws and perpetuate harmful practices.
Preventing Female Foeticide with AI-Powered Fetal-Sex Censoring
To combat the declining child sex ratio in India, our research introduced a novel computer-vision AI module that automatically detects and obscures anatomies associated with sex-selective scanning in live ultrasound feeds.
- Real-Time Physiological Detection: A CNN, trained on thousands of annotated frames, identifies markers of fetal-sex determination with over 98% accuracy.
- Automatic Censoring: The system immediately applies pixel-level blurring to relevant regions, preserving diagnostic clarity while preventing gender reveal.
- Seamless Compliance: This AI layer operates within our security framework, preventing misuse at the point of care and generating tamper-proof audit logs.
A Research-Backed, Four-Tier AI Security Framework
Our solution integrates advanced algorithms into a unified platform operating at four layers:
- Account-Authenticated Usage: Each device is cryptographically bound to authorized practitioners.
- Real-Time Physiological Censoring: The proprietary AI model automatically blurs fetal-sex markers in live streams.
- Suspicious Activity Detection: ML classifiers monitor scan metadata and flag non-compliant usage patterns.
- Smart PC-PNDT Dashboards: Interactive dashboards provide authorities with real-time, geo-located compliance data.
Research & Innovation Highlights
- Computer Vision for Compliance: Our censoring module achieves over 98% detection accuracy, ensuring robustness and patient safety.
- Anomaly Detection at Scale: Unsupervised learning adapts to varying clinical practices while maintaining low false-positive rates.
- Privacy-Preserving Architecture: Image data is processed in-memory on a secure cloud cluster, with de-identified metadata for analytics.
- Geo-Spatial Enforcement: Real-time location data allows regulators to deploy targeted inspections, reducing manual audit workloads.
Impact & Next Steps
- Expanded Rural Coverage: AI safeguards enable confident deployment of portable USG units in primary health centers.
- Accelerated Compliance: Automated alerts have cut violation investigation times by over 50% in pilot districts.
- Ongoing R&D: We are exploring edge-AI optimizations and federated learning to continually refine models.
By uniting cutting-edge AI research with pragmatic compliance tools, our platform exemplifies how innovation can drive both social good and regulatory integrity.
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