ML based Motion Tracking and Synthetic MR Motion Image Generator
tagsim/ contains code used to generate motion images, and perform a Bloch
simulation to create MR images with proper contrast/features.
torch_tag/ contains the pyTorch implementation of the tracking network and
code used to train the network.
Software to generate pseudo random deformation MR images. Includes full image deformations and cardiac-like deformations, as well as a GPU accelerated Bloch simulator to generate MR images.
Demo Jupyter notebooks are in the tagsim/notebooks folder.
Installation: This code requires a C library to be built for gridding. Running python setup.py build_ext --inplace in the tagsim folder should build everything. If you are using XCode to on Mac for C compiling, replace setup.py with setup_xcode.py (this disables openMP because stock Mac XCode doesn't support it).
Software containing the neural network for tracking MR images. The full network implementation and pre-trained network are included, as well as a demo of its usage on an example dataset. Machine learning is implemented with pyTorch.
Demo Jupyter notebooks are in the torch_track/notebooks folder.
A pre-train network for grid-tagged tracking is in the tagtorch_tracksim/network_saves folder.
Installation: No special installation is required for this software, other than installing required dependencies as they come up.