deepbet 0.0.1

Fast brain extraction using neural networks

This is the official implementation of the deepbet paper.

deepbet is a neural network based tool which achieves state-of-the-art results for brain extraction of T1w MR images of healthy adults while taking ~1 second per image.

Usage

After installation, there are three ways to use deepbet

1. deepbet-gui runs the Graphical User Interface (GUI)

2. deepbet-cli runs the Command Line Interface (CLI)

3. Run deepbet directly in Python

from deepbet import run_bet

input_paths = ['path/to/sub_1/t1.nii.gz', 'path/to/sub_2/t1.nii.gz']
brain_paths = ['path/to/sub_1/brain.nii.gz', 'path/to/sub_2/brain.nii.gz']
mask_paths = ['path/to/sub_1/mask.nii.gz', 'path/to/sub_2/mask.nii.gz']
tiv_paths = ['path/to/sub_1/tiv.csv', 'path/to/sub_2/tiv.csv']
run_bet(input_paths, brain_paths, mask_paths, tiv_paths, threshold=.5, n_dilate=0, no_gpu=False)

Besides the input paths and the output paths

• brain_paths: Destination filepaths of input nifti files with brain extraction applied
• mask_paths: Destination filepaths of brain mask nifti files
• tiv_paths: Destination filepaths of .csv-files containing the total intracranial volume (TIV) in cm³
  • Simpler than it sounds: TIV = Voxel volume * Number of 1-Voxels in brain mask

you can additionally do

• Fine adjustments via threshold: deepbet internally predicts values between 0 and 1 for each voxel and then includes each voxel which is above 0.5. You can change this threshold (e.g. to 0.1 to include more voxels).
• Coarse adjustments via n_dilate: Enlarges/shrinks mask by successively adding/removing voxels adjacent to mask surface.

and choose if you want to use GPU (NVIDIA and Apple M1/M2 support) for speedup

• no_gpu: deepbet automatically uses NVIDIA GPU or Apple M1/M2 if available. If you do not want that set no_gpu=True.

Installation

pip install deepbet
conda install -c anaconda pyqt=5.15.7

Citation

If you find this code useful in your research, please consider citing:

@inproceedings{deepbet,
Author = {Lukas Fisch, Stefan Zumdick, Carlotta Barkhau, Daniel Emden, Jan Ernsting, Ramona Leenings, Kelvin Sarink, Nils R. Winter, Udo Dannlowski, Tim Hahn},
Title = {fastbet: Fast brain extraction of T1-weighted MRI using Convolutional Neural Networks},
Journal  = {Imaging Neuroscience},
Year = {2023}
}