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DKFZ-RadOpt/pyRadPlan-dosecalc-Det-VHEE-200-lung
pyRadPlan-dosecalc-Det-VHEE-200-lung is a machine learning model from DKFZ-RadOpt. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as bsd-3-clause.
Deterministic VHEE (Very High Energy Electron) dose predictor for lung cases, trained for a single fixed beam energy of 200 MeV (ConvBayesnew architecture, single forward pass). Given a CT cuboid and a beamlet, predic…
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Updated Sep 29, 2026
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From the Hugging Face model README
Deterministic VHEE (Very High Energy Electron) dose predictor for lung cases, trained for a
single fixed beam energy of 200 MeV (ConvBayes_new architecture, single forward pass).
Given a CT cuboid and a beamlet, predicts a local physical dose cuboid.
Usable directly as the AIBeamletEngine dose-calculation engine in
pyRadPlan:
pln.prop_dose_calc = {"engine": "AIBeamlet", "model": "DKFZ-RadOpt/pyRadPlan-dosecalc-Det-VHEE-200-lung"}
VHEE plans use one fixed energy per beam. Companion models cover the other supported
energies — pyRadPlan-dosecalc-Det-VHEE-100-lung and pyRadPlan-dosecalc-Det-VHEE-150-lung;
load the one that matches pln.prop_stf["energy"].
Follows the pyRadPlan model contract (pyRadPlan.ai.modelhub):
| File | Purpose |
|---|---|
model.py | ConvBayes_new network definition |
preprocessor.py | ConvDoseSinglePreprocessor — input assembly + forward pass + output scaling |
weights.safetensors | Trained weights |
model_config.json | Declarative model/preprocessing/dose-calc configuration |
physical_dose — predicted physical dosePredictions outside this range are not guaranteed to be accurate; AIBeamletEngine warns
when the plan falls outside the declared range.
Security note: loading this model executes
model.py/preprocessor.pyshipped in this repository.pyRadPlan.ai.modelhub.load_modelrequires an explicit opt-in for hub models (trust_remote_code=TrueorPYRADPLAN_AI_MODELHUB_TRUST_REMOTE_CODE=1);AIBeamletEngineruns the downloaded copy directly.