This is a direct Python implementation of the Low Field Simulator from the Magnetic Resonance Engineering Laboratory at USC.
For example usage take a look at fastMRI_to_lowfield.py that converts the fastMRI knee dataset (1.5T/3.0T) to simulated low field data.
The fastMRI dataset can be downloaded here.
Low Field Sim Py:
- python >= 3.7.6
- numpy >= 1.19.2
fastMRI to low field:
- h5py >= 2.8.0
- xmltodict > 0.12.0
To simulate low field noise on fastMRI data, set INPUT_PATH to the folder containing .h5
files of the dataset, OUTPUT_PATH to an empty folder where the output will be saved and B_LOW to the desired low field strength. Then run
python3 fastMRI_to_lowfield.py --input-path INPUT_PATH --output-path OUTPUT_PATH --B-low B_LOW