| Name | mrtwin JSON |
| Version |
0.1.3
JSON |
| download |
| home_page | None |
| Summary | Collection of virtual objects for numerical MR experiments. |
| upload_time | 2024-09-12 09:08:01 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.10 |
| license | None |
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brainweb
mri
download
data
|
| VCS |
 |
| bugtrack_url |
|
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No requirements were recorded.
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MRTwin
======
MRTwin is a collection of virtual objects for numerical MR experiments.
|Coverage| |CI| |CD| |License| |Codefactor| |Sphinx| |PyPi| |Black| |PythonVersion|
.. |Coverage| image:: https://infn-mri.github.io/mrtwin/_static/coverage_badge.svg
:target: https://infn-mri.github.io/mrtwin
.. |CI| image:: https://github.com/INFN-MRI/mrtwin/workflows/CI/badge.svg
:target: https://github.com/INFN-MRI/mrtwin
.. |CD| image:: https://github.com/INFN-MRI/mrtwin/workflows/CD/badge.svg
:target: https://github.com/INFN-MRI/mrtwin
.. |License| image:: https://img.shields.io/github/license/INFN-MRI/mrtwin
:target: https://github.com/INFN-MRI/mrtwin/blob/main/LICENSE.txt
.. |Codefactor| image:: https://www.codefactor.io/repository/github/INFN-MRI/mrtwin/badge
:target: https://www.codefactor.io/repository/github/INFN-MRI/mrtwin
.. |Sphinx| image:: https://img.shields.io/badge/docs-Sphinx-blue
:target: https://infn-mri.github.io/mrtwin
.. |PyPi| image:: https://img.shields.io/pypi/v/mrtwin
:target: https://pypi.org/project/mrtwin
.. |Black| image:: https://img.shields.io/badge/style-black-black
.. |PythonVersion| image:: https://img.shields.io/badge/Python-%3E=3.10-blue?logo=python&logoColor=white
:target: https://python.org
Features
--------
- **Virtual Phantoms:** A collection of sparse (fuzzy and crisp) and dense phantoms for quantitative MRI based on different anatomical models (Shepp-Logan, Brainweb database, Open Science CBS Neuroimaging Repository database) and different tissue representations (single pool, two- and three-pools).
- **Field Maps:** Routines for generation of realistic field maps, including B0 (based on input phantom susceptibility), B1 (including multiple RF modes) and coil sensitivities.
- **Motion patterns:** Markov chain generated rigid motion patterns (both for 2D and 3D imaging) to simulate the effect of motion on MR image quality.
- **Gradient System Response:** Generate Gaussian-shaped gradient response function with linear phase components to simulate k-space trajectory shift and deformation due to non-ideal gradient systems.
Installation
------------
MRTwin can be installed via pip as:
.. code-block:: bash
pip install mrtwin
Basic Usage
-----------
Using MRTwin, we can quickly create a Shepp-Logan phantom,
the corresponding static field inhomogeneity map and a set
of coil sensitivity maps as follows
.. code-block:: python
import mrtwin
# 2D Shepp-Logan phantom
phantom = mrtwin.shepplogan_phantom(ndim=2, shape=256).as_numeric()
# B0 map
b0_map = mrtwin.b0field(phantom.Chi)
# Coil sensitivity maps
smaps = mrtwin.sensmap(shape=(8, 256, 256))
This allow us to quickly simulate, e.g., a fully-sampled multi-coil Cartesian GRE experiment
as:
.. code-block:: python
import numpy as np
TE = 10.0 # ms
rate_map = 1e3 / phantom.T2s + 1j * 2 * np.pi * b0_map
gre = smaps * phantom.M0 * np.exp(-rate_map * TE * 1e-3)
This can be coupled with other libraries (e.g., `MRI-NUFFT <https://github.com/mind-inria/mri-nufft>`_)
to simulate more complex MR sequences (e.g., Non-Cartesian and sub-Nyquist imaging).
Development
~~~~~~~~~~~
If you are interested in improving this project, install MRTwin in editable mode:
.. code-block:: bash
git clone git@github.com:INFN-MRI/mrtwin
cd mrtwin
pip install -e .[dev,test,doc]
Related projects
----------------
This package is inspired by the following excellent projects:
- Brainweb-dl <http://github.com/paquiteau/brainweb-dl>
- Phantominator <https://github.com/mckib2/phantominator>
- SigPy <https://github.com/mikgroup/sigpy>
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