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@@ -11,11 +11,20 @@ The figure shows a predicted liver mask with the corresponding patient CT in 3DS
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  The LITS dataset can be accessible from [here](https://competitions.codalab.org), and the corresponding paper for the challenge (Bilic. P et al.. (2019). The Liver Tumor Segmentation Benchmark (LiTS). https://arxiv.org/abs/1901.04056). If trained model is used please cite this paper.
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  ### Usage:
 
 
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  ```
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  git clone https://github.com/andreped/livermask.git
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  cd livermask
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- python -m venv venv
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- python -m pip install -r /path/to/requirements.txt
 
 
 
 
 
 
 
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  cd livermask
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  python livermask.py "path_to_ct_nifti.nii" "output_name.nii"
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  ```
 
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  The LITS dataset can be accessible from [here](https://competitions.codalab.org), and the corresponding paper for the challenge (Bilic. P et al.. (2019). The Liver Tumor Segmentation Benchmark (LiTS). https://arxiv.org/abs/1901.04056). If trained model is used please cite this paper.
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  ### Usage:
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+
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+ 1) Clone repo:
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  ```
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  git clone https://github.com/andreped/livermask.git
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  cd livermask
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+ ```
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+ 2) Create virtual environment and intall dependencies:
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+ ```
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+ virtualenv -ppython3 venv
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+ source venv/bin/activate
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+ pip install -r /path/to/requirements.txt
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+ ```
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+ 3) Run livermask method:
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+ ```
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  cd livermask
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  python livermask.py "path_to_ct_nifti.nii" "output_name.nii"
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  ```