Deep Learning for Automatic Segmentation of Vestibular Schwannoma: A Retrospective Study from Multi-Centre Routine MRI -- Deep learning models

These are zipped folders containing all models trained with nnU-Net for the journal publication:

Deep Learning for Automatic Segmentation of Vestibular Schwannoma: A Retrospective Study from Multi-Centre Routine MRI

The Zenodo upload contains the following files:

• Multi-Centre-Routine-Clinical-(MC-RC)-models.zip
  • Models trained on the MC-RC dataset
• Single-Centre-Gamma-Knife-(SC-GK)-models.zip
  • Models trained on the SC-GK dataset
• run_inference.sh
  • a command line script to run inference with the models
• example_input_images.zip
  • example images to test the inference

To run inference, the nnU-Net python package must be installed. This can be done with the following command:

pip install nnunet

To run inference on images located in a folder, unzip the zipped folders and run the run_inference.sh script. At the beginning of the script, the user can choose the model, the input path and the output path.