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Overview

Developed a medical imaging SaaS platform for radiologists with AI-powered segmentation using pre-trained U-Net models. Implemented real-time collaborative annotation supporting 10+ concurrent radiologists per case with conflict resolution.

Key Features

DICOM viewer with AI-assisted ROI detection

Real-time collaborative annotations (WebRTC)

HIPAA-compliant data handling architecture

ML model serving via FastAPI

Annotation version control

Architecture

FastAPI microservices, PyTorch model serving with TorchServe, WebRTC for real-time collaboration, encrypted S3 storage with pre-signed URLs, audit logging for compliance.

Technology Stack

ReactPythonFastAPIPyTorchWebRTCPostgreSQLDockerAWS S3

Detailed technical blog post coming soon. This project showcases production-grade architecture and real-world problem solving.

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