CMR Segmentation

Browser-based cardiac MRI segmentation — all processing runs locally
No data leaves your device
MobileUNetV2 (2.09M params, 8 MB) — trained with knowledge distillation




Cine Sample Scar Sample
Load a model and DICOM series to begin.
Input
Segmentation Overlay
LV Cavity
LV Myocardium
RV Cavity
How it works: The cine segmentation model (MobileUNetV2, 8 MB) auto-loads on page visit. Upload DICOM files, and the app parses headers, normalizes images, resamples to 224×224, runs inference via ONNX Runtime Web (WebAssembly), and displays segmentation overlays. All computation happens in your browser — no data is transmitted to any server.

Supported formats: Cine (multi-phase 2D) or Scar/LGE (single-phase 2D). Select all DICOM files belonging to one series.

Output: Click "Download Results" to get a ZIP with NIfTI volumes, CSV measurements, and a README.

Try it: Click "Cine Sample" above to download a sample cine DICOM series (1 short-axis slice, 25 phases). Unzip, then select all .dcm files in the DICOM file picker.

Model: MobileUNetV2 with knowledge distillation (T=3.0, W=0.99). Trained on ACDC + M&Ms datasets (633 subjects, 4 scanner vendors). Mean Dice: 0.883 (LV cavity: 0.921, LV myocardium: 0.851, RV cavity: 0.875).

Reference: Feng X, Huang G, Meyer CH. CPU-based fast cardiac cine MRI segmentation using lightweight CNNs and knowledge distillation. NMR in Biomedicine (under review).