BVmaths is a Python utility for performing arithmetic and thresholding operations on NIFTI (.nii.gz) files, similar to the functionality offered by FSL's fslmaths tool.
One advantage is that it runs directoly on python using only numpy and nibabel libraries, and can therefore be run on Windows easily.
- Supports of operations such as addition, subtraction, multiplication, division, binarization, thresholding, and upper thresholding.
- Automatically appends
.nii.gzextension to filenames if not provided. - Command-line interface for easy integration into processing pipelines.
To use BVmaths, you only need to have a working Python with nibabel and numpy libraries available.
However, if you also plan on using the rest of our BV-RADS tools, we recommend installing the full environment with the necessary libraries:
You will need to have Conda installed. You can use either Anaconda or Miniconda.
Download and install Anaconda or Miniconda.
Clone the BVmaths repository from GitHub:
git clone https://github.com/BV-RADS/BV-Maths.git
Navigate to the cloned repository and create a Conda environment using the environment.yml file:
cd BV-Maths
conda env create -f environment.yml
Once the environment is created, activate it:
conda activate BV-RADS
To use BVmaths, run the script with the desired operation and operands.
Usage: python BVmaths.py <image.nii.gz> [operations and inputs] <out.nii.gz>
Operations:
-mul : Multiply by following input (image or number)
-div : Divide by following input (image or number)
-add : Add following input (image or number)
-sub : Subtract following input (image or number)
-bin : Binarize image (set all voxels >0 to 1)
-thr : Threshold image (zero voxels below following number)
-uthr : Upper threshold (zero voxels above following number)
Example:
python BVmaths.py image1.nii.gz -mul image2.nii.gz -add 5 -bin out.nii.gz
python BVmaths.py image1.nii.gz -thr 2.0 -uthr 3.5 -bin out.nii.gz
For detailed usage instructions, run:
python BVmaths.py -h