AI HEALTHCARE DIAGNOSTICS
vision
AI Medical Imaging & Diagnostic Assistant
A certified medical AI system utilizing 3D UNet neural networks to assist radiologists in analyzing X-Rays, MRIs, and CT scans for early detection of abnormalities with high precision.
# Deep Learning# DICOM Image# UNet Segmentation# TensorFlow# Monai
Contract formatContract development
Development system6 people
Development period6 months
Key Features
Core System Capabilities
Optimized modular design for both End-Users and Enterprise Management Admin
01
Radiologist side
- DICOM medical image viewer & PACS sync
- Automated lesion detection heatmap overlay
- 3D organ segmentation visualization
- Diagnostic report auto-draft generation
- Doctor review & digital sign-off
5 features
02
Medical AI Model side
- 3D UNet & ResNet deep neural pipeline
- High-resolution DICOM pre-processing
- Multi-class abnormality classification
- HIPAA & DICOM standard compliance
4 features
03
Hospital Admin side
- PACS / HIS server integration settings
- Diagnostic confidence threshold tuning
- Doctor audit & AI performance dashboard
- Medical data security & access logs
4 features
Development Scope
Project Life Cycle & Phases
Phase 01
Requirement definition
Phase 02
UI/UX design
Phase 03
Medical AI model training
Phase 04
Development
Phase 05
Unit / Integration testing
Phase 06
Operation and Maintenance
Tech Stack Architecture
Technologies Used in Project
Languages & Core Frameworks
Python, C++, PyTorch, MONAI
AI Tools & GenAI Models
3D UNet, Claude 3.5 Sonnet (Medical), Antigravity Diagnostic Model
Databases & Vector Storage
Orthanc DICOM Server, PostgreSQL
Infrastructure & Cloud Services
NVIDIA DGX Station, AWS HealthImaging
READY TO TRANSFORM?
Ready to Launch Your Enterprise Web Project?
DIPro engineering team is ready to consult optimal solutions and build outstanding products for you.