This repository contains the code and models used for the final submission in the AutoPET III Challenge. This repository is released under the MIT License.
Our method uses a classifier to differentiate between FDG and PSMA tracers. It then runs inference on the PET/CT using a tracer-specific nnU-Net ensemble. The paper is available at: https://arxiv.org/pdf/2409.12155
- FDG Model: nnUNet ensemble specifically trained with FDG PET data.
- PSMA Models: Includes two models trained on PSMA PET data:
- A standard nnU-Net architecture.
- A nnU-Net model with a Residual Encoder architecture.
- Tracer Classifier: A model trained to classify the input as either FDG or PSMA tracer. This classifier can be used if the used tracer is unknown.
All model weights are available under https://drive.google.com/file/d/1nY7ciiJPcfxtv1XFpY-eWsmBkxfTSJez/view. They include the following files/folders:
- FDG Model: Checkpoints are found in the
Dataset001_fdgweighted
folder. - PSMA Models:
- Standard nnU-Net: Located in
Dataset002_psmaweighted
. - Residual Encoder nnU-Net: Located in
Dataset003_psmaweighted
.
- Standard nnU-Net: Located in
- Tracer Classifier: Model weights for the tracer classifier are available in
tracer_classifier.pt
.