A toolbox for MRI Gradient Optimization (GrOpt)
- Fast numerical optimizations for MR gradient waveform design (typically 1-100ms).
- Core libraries built completely in C for native integration in pulse sequences.
- Python and Matlab wrappers for easy prototyping.
- Flexible constraint system to enable a range of application.
- Constraints applied in a modular fashion, so adding additional ones is relatively straightforward.
The optimization is written in C and can be found in the src/ directory.
A very basic idea of how to compile for C is included in src/make.txt, however modifications would need to made for input and output as it only runs a test case when run in C. For easier usage use one of the wrappers:
The Python module has been tested primarily with Anaconda and Python 3.7, though it should work with any type of Python environment.
The setup.py file will build the python module. To build you can run
python setup.py build_ext --inplacefrom within the python/ directory.
This will use Cython to generate the source files for a Python module, and then compile it within the GrOpt folder. For MacOS this procedure requires Xcode. For Windows you may need a Visual Studio compiler (the free 2019 community version works just fine). Some common binaries are included in the repository, which should work without any compilation for most.
Assuming you have mex setup correctly (check with mex -setup), the two main functions can be compiled by simply running the make.m script.
Example usage cases are provided for the Python and Matlab wrappers. Examples for C applications are shown at the bottom of src/optimize_kernel.c
Demos for Python are all in the form of Jupyter notebooks (.ipynb files) in the ./python/ folder. Running jupyter notebook in the folder will get you started. Examples show diffusion and non-diffusion gradient design, and most combinations of constraints.
Demo Matlab scripts start with demo_*, are in the ./matlab/ folder, and can be run as is to see some example usage cases.
Further documentation, including descriptions of all constraints and their arguments and units, can be found at http://gropt.readthedocs.io