HD-CTBET is a fork of HD-BET repository, but targeted for CT BET rather than MRI-based. For the original repo, see https://github.com/MIC-DKFZ/HD-BET and the original publication:
Isensee F, Schell M, Tursunova I, Brugnara G, Bonekamp D, Neuberger U, Wick A, Schlemmer HP, Heiland S, Wick W, Bendszus M, Maier-Hein KH, Kickingereder P. Automated brain extraction of multi-sequence MRI using artificial neural networks. Hum Brain Mapp. 2019; 1–13. https://doi.org/10.1002/hbm.24750
- Clone this repository:
git clone https://github.com/CAAI/HD-CTBET
- Go into the repository (the folder with the setup.py file) and install:
cd HD-CTBET pip install -e . - Per default, model parameters will be downloaded from zenodo to ~/hd-bet_params. If you wish to use a different folder, open
HD_CTBET/paths.py in a text editor and modify
folder_with_parameter_files
hd-ctbet -i INPUT_FILENAMEINPUT_FILENAME must be a nifti (.nii.gz) file containing 3D MRI image data.
For batch processing it is faster to process an entire folder at once as this will mitigate the overhead of loading and initializing the model for each case:
hd-ctbet -i INPUT_FOLDER -o OUTPUT_FOLDERThe above command will look for all nifti files (*.nii.gz) in the INPUT_FOLDER and save the brain masks under the same name in OUTPUT_FOLDER.
HD-CTBET has CPU support. Running on CPU takes a lot longer though and you will need quite a bit of RAM. To run on CPU, we recommend you use the following command:
hd-ctbet -i INPUT_FOLDER -o OUTPUT_FOLDER -device cpu -mode fast -tta 0This works of course also with just an input file:
hd-ctbet -i INPUT_FILENAME -device cpu -mode fast -tta 0The options -mode fast and -tta 0 will disable test time data augmentation (speedup of 8x) and use only one model instead of an ensemble of five models for the prediction.
For more information, please refer to the help functionality:
hd-ctbet --help