BIDS to NiftyTorch: data preparation for deep learning.
niftytorchprep
command-line interface tool helps you prepare your data for niftytorch training. It check if BIDS format of your data is correct and transforms it
into the format that is coherent with deep learning models training.
pip install git+https://github.com/NiftyTorch/ohbm-hackthon2020.git
Or download this repository and call:
python setup.py install
$ niftytorchprep --help
Usage: niftytorchprep [OPTIONS] COMMAND [ARGS]...
NIFTYTORCHPREP helps to get your data ready for *niftytorch* training. You
can browse through your options below. Each one has respective help
function.
Options:
--help Show this message and exit.
Commands:
bids-files Print types of files and their number per folder.
bids-totraining Takes data from BIDS_DIR and organises it in a training...
bids-validate Basic BIDS verification.
qc-anat Runs Quality Control (T1) from visualqc package and...
qc-func Runs Quality Control (Functional) from visualqc package...
qc-getvisualqc Installs visualqc from PIP.
Here is an example that splits the data from various participants in BIDS format among: training, test and validation folders:
niftytorchprep bids-totraining my_bids_data/ my_output_to_dl/ gender --test 0.2 --val 0.1
To get help for a specific option, call for example:
niftytorchprep bids-totraining --help
See it in action:
Dominik Krzemiński @dokato
Cardiff University Brain Research Imaging Centre
Sara Morsy @SaraMorsy
Faculty of Medicine, Tanta University, Egypt
Kaori Lily Ito @kaoriito
Neural Plasticity & Neurorehabilitaiton Laboratory, University of Southern California
This project has been initiated at OHBM Hackthon 2020.