Accelerating Radiograph Reports with Complete Privacy.
Radiology in India is running on
borrowed time.
| Modality | Indian Avg TAT | Weekly Avg Cases (India) |
|---|---|---|
| X-ray | 4–12 Hr | 1100–1300 |
| Ultrasound | Report on site | 350–450 |
| CT-Scan (Emergency) | 30–60 min | 200–300 |
| CT-Scan (Routine) | 4–8 Hr | 200–300 |
| MRI | 12–25 Hr | 80–120 |
Chronic Radiologist Shortage
Practicing vs. Needed radiologists (2000→2024). Extremely overworked doctors failing to meet the WHO 1:10k standard.
The Cloud AI Bottleneck
- • Severe Data Privacy (DPDP) risks
- • Constant high-bandwidth dependency
- • Frequent upload failures
We propose a secure, hand-held edge device.
Automating tedious diagnostic tasks at the absolute physical edge to drastically reduce radiologist burnout, without sending a single pixel to the cloud.
Ingestion
Seamless DICOM file transfer directly from modality to the EdgeRad device via secure local network.
AI Triage
AI instantly processes the scan offline, flagging abnormalities and critical anomalies for priority review.
Selection
Radiologist refers to pathologies on the same interface and selects findings or orders needed studies.
Reporting
Instant generation of high-accuracy draft reports ready for final radiologist verification and sign-off.
Current State of Work
POC — Image Enhancement
Algorithm StatusPOC — Feature Extraction
Segmentation StatusIPR (Intellectual Property)
Process of enhancing images (all modalities) + process of extracting features (per modality).
Minimum Viable Product (MVP)
Full hardware and software stack integration.
Engineering Features
Multi-Modality Support
Legacy Device Support
Edge Device
(100% offline)
Supports Industrial Standards
Privacy First
Intuitive User Interface
Designed with Doctors, for Doctors
IIT Guwahati
AIIMS Guwahati