This is a collection of potentially useful modeling resources provided by the openCARP user community. If you have something to contribute, please let us know by filling this form. If you have questions regarding the resources, please refer to the point of contact described in the linked pages. If you have questions regarding the use of these resources in openCARP, please use the Question2Answer system
To convert meshes to openCARP file formats, meshtool is often the method of choice.
A bi-atrial statistcial shape model and 100 instances derived from the model. Volumetric bi-atrial meshes as vtk files, which were augmented in a post-processing step with a homogeneous wall thickness, fiber orientation (doi:10.1016/j.cma.2020.113468), intra-atrial bridges and material tags so that they are ready to use for electrophysiological simulations of atrial signals.
The bi-ventricular statistical shape model by Bai et al. 2015 (doi:10.1016/j.media.2015.08.009) was used to derive 100 simulation-ready instances. The ventricles were connected, the RV was clipped consistently, homogeneous RV wall-thickness was added, surfaces were merged and volumetric meshes generated. Details can be found in the description on Zenodo.
Link to resource: doi:10.5281/zenodo.4419783
24 whole-heart meshes based on imaging in heart failure patients. Volumetric meshes with region labels and annotated rule-based fiber angles and ventricular coordinates.
The CEMRG model collection currently includes healthy control 4 chamber meshes, 2D atria with DT-MRI fibres, 3D atria with fibres, ventricles with scar and 1000 synthetic four chamber hearts.
Link to resource: Website
This section does not cover general purpose meshing tools but pipelines targeted at openCARP use cases and file formats.
Typical modeling workflows involve a multitude of interactive mesh manipulation steps, rendering model generation expensive. Meshtool is software specifically designed for automating all complex mesh manipulation tasks emerging in such workflows by implementing algorithms for tasks describable as operations on label fields and/or geometric features. Meshtool can also convert a number of input format to openCARP mesh files.
Python code to build a simulation-ready 3D mesh from clinical CARTO mapping data. It provides control over mesh resolution, conduction velocity distribution and the definition of non-conductive regions.
Link to resource: GitHub
AugmentA (Augmented Atrial model Generation Tool) is a highly automated framework which, starting from clinical geometrical data, provides ready-to-use atrial personalized computational models. AugmentA consists firstly of a pre-processing step applied to the input geometry. Secondly, the atrial orifices are identified and labelled using only one reference point per atrium. If the workflow includes fitting a statistical shape model (SSM) to the input geometry, this is first rigidly aligned with the given mean shape and finally a non-rigid fitting procedure is applied. AugmentA automatically generates the fiber orientation using a Laplace-Dirichlet-Rule-based-Method.
RESILIENT is a rule-based atrial fiber generator for generating bi-atrial fibers and interatrial bridges. The algorithm works with triangle, terahedron and voxel meshes. The fibers are based on 22 seedpoints: 9 in the right atrium and 13 in the left atrium.
Independent implementation of the Laplace Dirichlet Rule-Based ventricular fiber algorithm by Bayer et al. 2015 (doi:10.1007/s10439-012-0593-5). Both the algorithm as described in the publication by Bayer et al. as well as an adaptation with detail improvements are provided.
Link to resource: GitHub
MATLAB implementation to compute local coordinates on tetrahedral meshes of biventricular cardiac geometries. Also provided are functions to utilize the results for transferring data, standardized visualization of data and alignment of the heart with the global coordinate axes. Besides code to compute the Cobiveco coordinates (doi:10.1016/j.media.2021.102247), also code to compute the Universal Ventricular Coordinates as described in the publication by Bayer et al. 2018 (doi:10.1016/j.media.2018.01.005) is provided.
OpenEP is a cross-platform electroanatomic mapping data format and analysis platform for electrophysiology research. OpenEP Data Parsing Modules allow proprietary data formats from major electroanatomic mapping platforms to be converted into the OpenEP data format. Batch processing, command line and graphical interfaces are provided for importing data. OpenEP Data Analysis Modules are available that cover 90% of the analysis techniques in use in contemporary electrophysiology research. OpenEP is under active development with additional functionality being continually added during the course of the developers’ research. OpenEP is available in Matlab with Python and Unity versions under development
CemrgApp is a platform with custom image processing and computer vision toolkits for applying statistical, machine learning, and simulation approaches to cardiovascular data. Further software of the CEMRG group can be found on their website.