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Knee MRI Segmentation

nnU-Net cascade — automatic segmentation of 9 knee structures (patellar / femoral / tibial cartilage, medial & lateral meniscus, femur, tibia, patella) with per-structure volumes, cartilage thickness and meniscus morphometry.

Research tool — not a regulated medical device. Their results are not a diagnosis and can be wrong. Every result must be reviewed by a qualified clinician, who remains responsible for the clinical decision.

Source: nnU-Net

This model is heavy (GPU, ~1–2 min) and runs from the PACS worklist, not as a browser upload. Open a knee MRI study, choose AI → Knee analysis, and a labelled segmentation overlay appears in the OHIF viewer with a morphometry PDF attached to the study.

What it does

Segments cartilage, meniscus and bone on a knee MRI, then computes per-structure volumes, cartilage thickness statistics and meniscus height/volume. The overlay is a standard DICOM-SEG — it reformats to all planes and 3D in the viewer, exactly like the brain-tumor and spine modules.

Live example Sagittal knee MRI
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Sagittal knee MRI with the 9-structure AI overlay — drag to scroll slices, switch to 3D for the surfaces

Morphometry (example)

Femoral cartilage volume

7.46 mL

Medial meniscus

2.31 mL

Femoral cartilage thickness

1.1 mm

median 1.0 · p95 1.9

Segmented structures

Patellar cartilage 2.33 mL
Femoral cartilage 7.46 mL
Medial tibial cart. 1.89 mL
Lateral tibial cart. 1.64 mL
Medial meniscus 2.31 mL
Lateral meniscus 1.63 mL
Femur 148.18 mL
Tibia 98.52 mL
Patella 13.80 mL

Volumes measured on the example above — the same numbers the attached PDF report carries.

Report metrics

  • Volumes — per-structure volume (mL) for all 9 structures.
  • Cartilage thickness — mean / std / median / p5 / p95 (mm), measured across the cartilage layer: from the bone-cartilage interface to the articular surface. Research metric, not a validated clinical thickness.
  • Meniscus — height (mm) and volume (mL) for the medial and lateral meniscus.

How to run it

  1. Open the PACS worklist and find a knee MRI study.
  2. Click the AI menu on that row and choose Knee analysis.
  3. After a couple of minutes the labelled overlay appears in the OHIF Segmentation panel and a morphometry PDF is attached to the study.
Go to PACS worklist

Model: nnU-Net v2 cascade (Dataset500_KneeMRI, OAI-ZIB). Mean Dice 0.906 across 9 structures. Goyal et al., 2025.

This project is free. If you would like to help with hosting and development, you can donate in stablecoins — open the Donate page.

How to donate