Knee MRI Cartilage Segmentation

Overview

A fully automated AI-based for knee MRI cartilage segmentation and quantitative analysis. The platform integrates directly with hospital PACS, processes standard knee MRI protocols, and delivers accurate segmentation, morphometric measurements, 3D visualization, and structured clinical reports.

The Problem

Manual segmentation is time-consuming, subjective, inconsistent, and error-prone.

Our Solution

Fully automated AI-based segmentation integrated with PACS System, DICOM/NIfTI compatibility, and quantitative 3D visualization & reporting.

🖥️ Auto Data Retrieval & Protocol Selection

Protocol Detection

  • Automatically detects the 't2_de3d_we_sag_iso' imaging protocol.

Data Preparation & Format Conversion

  • Uses dcm2niix for DICOM → NIfTI conversion.
  • Reorients images to RAS+ orientation, resamples, and ensures compatibility with AI segmentation models.

This automated preprocessing stage ensures consistent data quality and format standardization, eliminating manual intervention and reducing processing errors while maintaining full compatibility with downstream AI segmentation models.

Volume & Morphometry Analysis

Segmented Structures

  • Femoral Cartilage
  • Tibial Cartilage

Calculated Metrics

  • Volume (cm³)
  • Voxel Count
  • Side Detection
  • Trend Analysis

Clinical Applications

  • Surgical planning
  • Osteoarthritis tracking
  • Recovery monitoring
  • Research