pyRadPlan-dosecalc-Det-proton-lung

Deterministic proton dose predictor (ConvBayes_new architecture, single forward pass). Given a CT cuboid and a bixel energy, predicts a local physical dose cuboid.

Loadable via pyRadPlan.ml.load_model and usable directly as the AIBeamletEngine dose-calculation engine in pyRadPlan:

pln.prop_dose_calc = {"engine": "AIBeamlet", "model": "pyRadPlan-dosecalc-Det-proton-lung"}

Repository contents

Follows the pyRadPlan ML model contract (pyRadPlan.ml):

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

Outputs

• physical_dose — predicted physical dose

Training assumptions

• Radiation mode: protons
• Energy range: 75–160 MeV
• Trained machine: Generic
• Sampling grid: 2 mm spacing, ±52 mm lateral range, depth range [-220, 100] mm

Predictions 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.py shipped in this repository (gated behind trust_remote_code, default True in pyRadPlan.ml).