liver-segmentation

LiTs Challenege Semantic Segmentation of Liver from CT Scans

Steps To Set Up

• Clone The Repository https://github.com/imatge-upc/liverseg-2017-nipsws
  Put in inside the current directory as shown here. Replace the 'seg_liver.py', 'seg_liver_train.py', seg_liver.py' files inside the cloned repository by the files provided here.

• Create a Folder

  • LiTS_database inside liverseg folder.
  • create a results folder insider liverseg folder
  • Download the weights from here and add them to train_files folder.

Steps To Get Predictions

• Process NIFTI Files python process_test_database.py dataset_folder_name
  Input - ‘volume_i_.nii’ files from the dataset_folder
  Output - ‘/LiTS_database/test_image_volumes/’

• Create a File Containing Path to Test Images python Create_test.py test_image_volumes
  Input - "liverseg-2017-nipsws/LiTS_database/folder_name" Output - liverseg-2017-nipsws/seg_DatasetList/test.txt

• Test the Trained Model Download the weights from here

python liverseg-2017-nipsws/seg_liver_test.py Input - ‘seg_DatasetList/test.txt'
Output - ‘liverseg-2017-nipsws/results’

Convert Multile Images Slices into a 3D Volume python npy_2_volume.py

Converts multiple .npy output slices into a single .npy volume for a particular case. Input - "liverseg-2017-nipsws/results/seg_liver"
Output - “liverseg-2017-nipsws/results/output_volumes/”