CASE STUDY DETAILS

Dockerized Orthopedic Imaging Platform

Project Type

Artificial Intelligence

Challenge

Fragmented Patient, Case Management

Domain

Healthcare / DevOps

Impact

Fully AI-powered orthopedic imaging platform

OVERVIEW

OrthoVision AI is a cloud-based orthopedic medical imaging platform designed to streamline fracture detection, clinical case management, and medical report generation.

The platform enables doctors, radiologists, hospital staff, and administrators to manage patients, clinical cases, DICOM imaging studies, AI-assisted diagnoses, and structured PDF reports through a centralized web application.

A key highlight of the project is its cloud-native AWS architecture with Terraform-managed infrastructure, Docker-ready services, and automated deployment workflows.

The application is hosted on AWS EC2 (Ohio – us-east-2) with managed PostgreSQL (RDS), Redis, S3 storage, and AWS Cognito authentication — delivering a secure, scalable, and production-ready healthcare imaging solution.

PROBLEM

Many orthopedic clinics & hospitals still face challenges such as

The objective was to develop a complete orthopedic imaging platform with AI fracture detection, while implementing a modern cloud DevOps architecture that automates deployment, improves reliability, and supports scalable AWS infrastructure.

  • Manual fracture assessment relying only on radiologist review
  • Fragmented patient and case management across disconnected systems
  • Difficulty handling DICOM medical images securely
  • Slow report generation and inconsistent documentation
  • No AI-assisted decision support for early fracture detection
  • Environment inconsistencies between development and production
  • Manual infrastructure provisioning without Infrastructure as Code
  • Limited audit visibility for healthcare compliance
SOLUTIONS

1. Complete Orthopedic Healthcare Management

  • Patient registration and medical history
  • Clinical case creation and lifecycle tracking
  • Doctor and staff management
  • Hospital and organization management
  • Role-based dashboards (Admin, Doctor, Radiologist, Staff)
  • Guided clinical workflow (Patient → Case → Upload → AI → Report)

3. DICOM Imaging & Clinical Workflow

  • In-browser DICOM viewer (Cornerstone.js)
  • Case-linked imaging studies
  • AI prediction results integrated into case detail
  • Medical report generation with clinical summary, findings, impression, and recommendations

5. Dockerized Deployment

  • Docker containerization for backend services
  • Docker Compose for local/dev environments
  • Consistent deployment environments across dev and production
  • Health checks and container restart policies
  • Simplified application management

7. Secure Healthcare Operations

  • Role-Based Access Control (RBAC) via Pundit policies
  • JWT + AWS Cognito authentication
  • Secure patient record management
  • Audit logging and activity tracking
  • Encrypted storage (S3, RDS, KMS)
  • HIPAA-oriented architecture design

2. AI-Powered Fracture Detection

  • DICOM / X-ray image upload via secure S3 presigned URLs
  • AI model inference for fracture vs. non-fracture classification
  • Confidence scoring and structured AI findings
  • Automatic medical report draft generation
  • Professional PDF medical note export

4. Infrastructure as Code (Terraform)

  • AWS infrastructure provisioning using Terraform
  • VPC with public/private/database subnets
  • EC2 application server provisioning
  • RDS PostgreSQL with encryption
  • ElastiCache Redis for caching and background jobs
  • S3 for DICOM and report storage
  • KMS encryption for data at rest
  • Cognito user pool for authentication
  • Security Groups and IAM role automation
  • Remote state in S3 with DynamoDB locking

6. Cloud Monitoring & Operations

  • CloudWatch log groups for backend and Nginx
  • CloudWatch agent on EC2 for centralized logging
  • Systemd service management for backend API
  • Nginx reverse proxy for frontend + API routing
APPROACH

Our Approach

Research & Planning

  • Orthopedic imaging workflow analysis
  • Clinical user role definition (Doctor, Radiologist, Admin, Staff)

System Design

  • Multi-role healthcare architecture
  • PostgreSQL database schema with UUID-based entities

Technical Implementation

  • React + TypeScript frontend (Vite, TailwindCSS)
  • Ruby on Rails 7.1 API backend
  • PostgreSQL + Redis integration

Deployment

  • GitHub source code repository
  • Terraform provisioning on AWS (us-east-2)
  • EC2 production hosting with Nginx

Final Delivery

  • Multi-role healthcare architecture
  • PostgreSQL database schema with UUID-based entities
SUCCESS AND IMPACT

What Was Achieved

  • Faster fracture assessment with AI assistance
  • Reduced manual report preparation time
  • Improved clinical workflow consistency
  • Centralized patient and case management
  • Repeatable infrastructure provisioning via Terraform
  • Simplified application maintenance on AWS
  • Increased deployment reliability and observability
  • Cloud-ready platform for hospitals and clinics

By Business

  • Healthcare Web Application Development
  • AI Medical Imaging Integration
  • DICOM Viewer Development
  • DevOps Engineering
  • Docker Containerization
  • Infrastructure as Code (Terraform)
  • AWS Cloud Deployment
  • PostgreSQL Database Architecture
  • Secure Authentication System (Cognito + JWT)
  • Cloud Infrastructure Design
  • Medical PDF Report Generation
  • CloudWatch Monitoring Setup