demeter-metamorphosis 0.2.4

Efficient and flexible optimization of metamorphoses in images

Demeter Metamorphosis - 0.2.4

(DiffEoMorphic METamorphic Regristration)

Package status : alpha. see Documentation slides

Demeter_metamorphosis is a library intended to perform Metamorphosis on images. It can perform efficient registration of images in 2D and 3D with or without topology differences. We propose a flexible framework to perform Metamorphosis with differents modeling choices. Are provided:

• The classic LDDMM registration method for registering image having the same topologies as described by Trouvé et al. or Beg's 2005 paper.
• The classic Metamorphosis registration method for mixing diffeomorphic transport with intensities additions as described in Younes's book "Shape and Diffeomorphisms" (2019).
• A Weighted Metamorphosis registration method to control the intensity addition locally as described by me in this paper
• A Constrained Metamorphosis registration method to control the intensity addition locally and guide the registration with a pre-computed vector field as described by me in my thesis. (paper comming soon)
• and more to come...

The library is designed to be flexible and allow the user to define custom data cost functions, custom norms on the residual, custom vector fields, and custom geodesic integrators. Feel free to contact me through github Issues if you have any questions or need help with the library.

Why the name Demeter ? Because in ancient Rome, Demeter was the goddess of agriculture. Isn't it the perfect protection for or vectors fields ?

The Metamorphic framework [Holm et al., 2009; Trouvé and Younes, 2005; Younes, 2019] can be seen as a relaxed version of LDDMM in which we add time-varying intensity variations are added to the diffeomorphic flow, therefore allowing for topological changes. The image evolution is not only modelled by deformation, we allow adding intensity at each time for every voxel, making topological changes possible. Metamorphosis is solved through an Hamiltonian formulation and the momentum control both the deformation and the intensity changes.

You can find more information on the documentation but also follow a rapid introduction in the following slides: slides

Installation

At the moment, demeter-metamorphosis is available on linux and macOS only. Windows user can use the WSL to install the package.

WSL setup (for Windows users):

WSL is a compatibility layer for running Linux binary executables natively on Windows 10 and Windows Server 2019. It is a feature of the Windows operating system that allows you to run a Linux distribution directly on Windows without using a virtual machine or container. So first install WSL and then you can follow the Unix installation steps.

Install wsl:

 wsl --install

You might need to restart your computer to finish the installation process.

Open a terminal wsl. After the installation is completed, open wsl, set up a password.

sudo apt update
sudo apt install python3-pip
sudo apt install python3.12-venv

For Unix systems, (Linux and macOS)

First I advise you to create a fresh virtual environment with conda or venv. With venv more...:

conda create -n demeter_env python=3.12
conda activate demeter_env

OR conda

python3.12 -m venv "demeter_env"
source "demeter_env"/bin/activate

The last line activate the virtual environment. Please ensure that you are in the virtual environment when you are using the package.

You are now ready to install the package. For a direct usage of demeter you can install the package with pip, if you want to have a

From pip

pip install demeter-metamorphosis

From source

If you want the development version or consider contributing to the codebase, you can also install scikit-shapes locally from a clone of the repository.

Then clone the repository with one of the github provided methods. For example, with html:

git clone https://github.com/antonfrancois/Demeter_metamorphosis.git

Finally navigate to the cloned repository and install the package with

cd Your/path/to/Demeter_metamorphosis
pip install -e .

The whole process can take up to 10 minutes depending on your internet connection, mainly because of the torch and nvidia driver installation.

Examples. and Jupyter Notebooks

You can see results and usage examples in the examples folder or at the [Example Gallery](https://antonfrancois.github.io/Demeter_metamorphosis/auto_examples/index.html:

Location where are stored the saved optimisation results

Demeter allows you to save registration results as metamorphosis objects to be able to reuse, restart, visualize, or analyze the results later. By default, we store them in the ~/.local/share/Demeter_metamorphosis/ folder on linux (may wary on other platforms). You can change the default location by setting the DEMETER_OPTIM_SAVE_DIR environment variable. in the .env file. To locate it you can use the following commands: (in a python file or in a ipython terminal)

import demeter
demeter.display_env_help()

Contact

You can email me at anton.francois [at] ens-paris-saclay.fr or check my website : antonfrancois.github.io/