Laplace-Dirichlet Rule-Based (LDRB) algorithm for assigning myocardial fiber orientations

A software for assigning myocardial fiber orientations based on the Laplace Dirichlet Ruled-Based algorithm.

Bayer, J.D., Blake, R.C., Plank, G. and Trayanova, N.A., 2012. A novel rule-based algorithm for assigning myocardial fiber orientation to computational heart models. Annals of biomedical engineering, 40(10), pp.2243-2254.(https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3518842/)

```python

Generate an example geometry using https://github.com/ComputationalPhysiology/cardiac_geometries

import cardiac_geometries # pip install cardiac-geometries import ldrb

geo = cardiacgeometries.mesh.createbivellipsoid(charlength=0.2)

Decide on the angles you want to use

angles = dict( alphaendolv=30, # Fiber angle on the LV endocardium alphaepilv=-30, # Fiber angle on the LV epicardium betaendolv=0, # Sheet angle on the LV endocardium betaepilv=0, # Sheet angle on the LV epicardium alphaendosept=60, # Fiber angle on the Septum endocardium alphaepisept=-60, # Fiber angle on the Septum epicardium betaendosept=0, # Sheet angle on the Septum endocardium betaepisept=0, # Sheet angle on the Septum epicardium alphaendorv=80, # Fiber angle on the RV endocardium alphaepirv=-80, # Fiber angle on the RV epicardium betaendorv=0, # Sheet angle on the RV endocardium betaepirv=0, # Sheet angle on the RV epicardium )

Convert markers to correct format

markers = { "base": geo.markers["BASE"][0], "lv": geo.markers["ENDO_LV"][0], "rv": geo.markers["ENDO_RV"][0], "epi": geo.markers["EPI"][0], }

Choose space for the fiber fields

This is a string on the form {family}_{degree}

fiberspace = "P2"

Compute the microstructure

fiber, sheet, sheetnormal = ldrb.dolfinldrb( mesh=geo.mesh, fiberspace=fiberspace, ffun=geo.ffun, markers=markers, **angles )

Store files using a built in xdmf viewer that also works for functions

defined in quadrature spaces

ldrb.fibertoxdmf(fiber, "fiber")

And visualize it in Paraview

```

Installation

pip

In order to install the software you need to have installed FEniCS (versions older than 2016 are not supported)

The package can be installed with pip. python3 -m pip install ldrb or if you need the most recent version you can install the source python3 -m pip install git+https://github.com/finsberg/ldrb.git

Issues with h5py

You might run into issues with incompatible version of h5py. To resolve this you can try to first uninstall the existing version python3 -m pip uninstall h5py and then reinstall h5py from source using the command python3 -m pip install h5py --no-binary=h5py

Conda

ldrb is also available on conda conda install -c conda-forge ldrb

Docker

If you don't already have FEniCS installed you can use one of the provided docker images, e.g docker pull ghcr.io/finsberg/ldrb:latest to pull the image and use the following command to start a container and sharing your current directory docker run --rm -v $PWD:/home/shared -w /home/shared -it ghcr.io/finsberg/ldrb:latest

Documentation

Documentation is hosted at http://finsberg.github.io/ldrb

Getting started

Check out the demos

License

ldrb is licensed under the GNU LGPL, version 3 or (at your option) any later version. ldrb is Copyright (2011-2019) by the authors and Simula Research Laboratory.

Contributors

Henrik Finsberg (henriknf@simula.no)