https://github.com/osbm/prostate158

https://github.com/osbm/prostate158

Last synced: over 1 year ago
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• Host: GitHub
• URL: https://github.com/osbm/prostate158
• Owner: osbm
• Created: 2023-07-23T20:48:59.000Z (about 3 years ago)
• Default Branch: master
• Last Pushed: 2023-08-09T17:04:36.000Z (almost 3 years ago)
• Last Synced: 2025-02-01T23:38:32.420Z (over 1 year ago)
• Language: Jupyter Notebook
• Size: 4.76 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          

## Create a virtual environment (optional)

This step is highly recommended. This way you wont have to deal with dependency and versioning issues.

```

python -m venv .venv

source ./.venv/bin/activate

```

## Install requirements

```

pip install -r requirements.txt

```

## Create nnunet dataset from Prostate158

```

python create_nnunet_dataset.py

```

Now you will have `nnUNet_raw` folder. By default it creates a dataset for t2 axial images as input and anatomy masks as output.

Now you can see [t2-to-anatomy-20-epoch.ipynb](t2-to-anatomy-20-epoch.ipynb) file to see how to train a fold.