Generate numerical phantoms.
python -m pip install phantominator
The goal is to have easy installation and usage for everyone. If something doesn’t work, please open an issue and/or submit a pull request. We’ll get it figured out.
pygrappa is an optional dependency required to run the phantominator.examples.radial_coil_sens example.
Python package for easy generation of numerical phantoms. I often need a simple image to try something out on. In MATLAB, I would use the phantom command to quickly get something to work with. In Python, it’s not always quite so easy, so I made this package that’s quick to install and use so there’s as little friction as possible. There are other implementations of Shepp-Logan available from other projects, but they are usually not as easy to install or include other things that I don’t want for this project.
This package offers both CT and MR versions.
Going forward, this module will support Python >= 3.8.
Also see the examples module and docstrings. The interface for CT phantom generation is similar to MATLAB’s phantom function.
Examples can be run as:
# python -m phantominator.examples.[example-name], e.g.: python -m phantominator.examples.shepp_logan
# CT phantom from phantominator import shepp_logan ph = shepp_logan(128) # MR phantom (returns proton density, T1, and T2 maps) M0, T1, T2 = shepp_logan((128, 128, 20), MR=True)
The Shepp-Logan 3D phantom has ellipsoids in [-1, 1] along the z-axis. The 2D Shepp-Logan exists at z=-0.25, so if we want just a subset along the z-axis with the first slice being the traditional 2D phantom, we can use the zlims option:
from phantominator import shepp_logan M0, T1, T2 = shepp_logan((64, 64, 5), MR=True, zlims=(-.25, .25))
We can also generate simple oscillating concentric circles:
# Dynamic (concentric circles), 20 time frames from phantominator import dynamic ph = dynamic(128, 20)
If we want to modify ellipse/ellipsoid parameters or we just want to see what they are. For example, we can get the MR ellipsoid parameters like this:
from phantominator import mr_ellipsoid_parameters E = mr_ellipsoid_parameters()
See docstrings for ct_shepp_logan, and mr_shepp_logan for how the array E is structured. It follows conventions from MATLAB’s phantom function.
Arbitrary k-space sampling is supported for the single coil 2D Shepp-Logan phantom:
# Given k-space coordinates (kx, ky), where kx and ky are 1D # arrays using the same unit conventions as BART's traj command, # we can find the corresponding k-space measurements: from phantominator import kspace_shepp_logan k = kspace_shepp_logan(kx, ky)
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