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Project description
Welcome to CMRsim!
CMRsim is a MRI - simulation framework that features bloch-simulations as well as analytic signal evaluations for moving objects with an easy to use API written in pure python. The computationally demanding calculations are implemented in TensorFlow2 and therefore are seamlessly executable on CPU and GPU environments, while also making efficient use of computational resources!
What makes CMRsim special?
CMRsim features bloch-simulations as well as simulations using analytical signal equations and even allows to combine elements of both.
Convenient support for moving particles!
Modularity that makes to designing comparative simulation experiments convenient.
Architecture and implementation that allows to easily include your own simulation modules.
Reproducibility by using versioned and documented open-source software.
Easily scalable to detailed digital phantoms
Installation
Pip
CMRsim can be installed using the python package manager pip
. The package can be found
in the registry of the repository hosted on the ETH-Gitlab instance
Versioning:
Stable release versions are denoted with the ususal major.minor
notation. Additionally,
development versions are constantly updated on solved issued and can be installed using the
major.minor.devX
notation
Installation in command line:
pip install cmrsim --extra-index-url https://__token__:<your_personal_token>@gitlab.ethz.ch/api/v4/projects/23798/packages/pypi/simple
Requirements
CMRsim does rely on functionality of 3 non-standard python stack packages:
TensorFlow: Pretty much all computationally heavy calculations.
Pyvista: For processing and visualizing graphs (e.g. 3D Velocity fields).
CMRseq: For defining MR-sequences used for Fourier-Encoding calculation and Bloch-simulation.
Further (already indirectly included) requirements are: -h5py~=2.10.0 -scipy>=1.4.1 -tqdm
Docker
For each major release a set of docker images are compiled and published in the container registry associated with repository. Within the docker images, all requirements are installed for simulation deployment.
Furthermore, there are three image-tags available. To use the pull the docker image use (e.g. for jupyter tag):
docker pull registry.ethz.ch/jweine/cmrsim/jupyter:latest
CPU
Based on the Tensorflow:…-cpu:latest docker image. Containing all cmrsim dependencies and cmrsim
GPU
Based on the Tensorflow:…-gpu:latest docker image. Containing all cmrsim dependencies and cmrsim
Jupyter
Based on the gpu:latest tag, but also includes an installation of jupyter-lab for interactive simulation / rendering.
Project details
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