TotalSegmentator MRI — Worker pipeline v2

Dataset852 nnU-Net V2 PlainConvUNet (fold 0, [64,64,64] patch / 3.0 mm iso spacing, 51-class TotalSegMRI labels). All compute (WASM + WebGPU) runs in a dedicated Web Worker — page stays responsive during inference.
How to use: ① Init WASM + model → ② Upload MR NIfTI (.nii / .nii.gz) → ③ Run → ④ Download. Anisotropic inputs (max/min spacing > 3×) go through host-side separate_z per-slice 2D B-spline + nearest-Z (matches nnU-Net exactly). Near-iso inputs use the faster GPU 3D B-spline path. Model weights are cached in IndexedDB on first load (66 MB); subsequent visits are offline-ready.

Log

Slice viewer

Canonical input (z-scored)
Predicted labels (51 classes)
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