Title | ||
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Modeling atrial fiber orientation in patient-specific geometries: a semi-automatic rule-based approach |
Abstract | ||
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Atrial myofiber orientation is complex and has multiple discrete layers and bundles. A novel robust semi-automatic method to incorporate atrial anisotropy and heterogeneities into patient-specific models is introduced. The user needs to provide 22 distinct seed-points from which a network of auxiliary lines is constructed. These are used to define fiber orientation and myocardial bundles. The method was applied to 14 patient-specific volumetric models derived from CT, MRI and photographic data. Initial electrophysiological simulations show a significant influence of anisotropy and heterogeneity on the excitation pattern and P-wave duration (20.7% shortening). Fiber modeling results show good overall correspondence with anatomical data. Minor modeling errors are observed if more than four pulmonary veins exist in the model. The method is an important step towards creating realistic patient-specific atrial models for clinical applications. |
Year | DOI | Venue |
---|---|---|
2011 | 10.1007/978-3-642-21028-0_28 | FIMH |
Keywords | Field | DocType |
semi-automatic rule-based approach,minor modeling error,fiber modeling result,atrial anisotropy,patient-specific model,patient-specific geometries,novel robust semi-automatic method,anatomical data,patient-specific volumetric model,atrial myofiber orientation,fiber orientation,realistic patient-specific atrial model,atrial fiber orientation,rule based,model error | Rule-based system,Anisotropy,Fiber,Simulation,Computer science,Algorithm,Patient-Specific Modeling | Conference |
Volume | ISSN | Citations |
6666 | 0302-9743 | 19 |
PageRank | References | Authors |
2.58 | 7 | 16 |
Name | Order | Citations | PageRank |
---|---|---|---|
Martin W. Krueger | 1 | 98 | 13.35 |
Viktor Schmidt | 2 | 19 | 2.58 |
Catalina Tobón | 3 | 25 | 10.20 |
F M Weber | 4 | 88 | 12.08 |
Lorenz Cristian | 5 | 893 | 100.01 |
David U. J. Keller | 6 | 59 | 8.52 |
H Barschdorf | 7 | 49 | 7.69 |
Michael Burdumy | 8 | 19 | 2.58 |
Peter Neher | 9 | 25 | 3.17 |
G Plank | 10 | 201 | 33.05 |
Kawal Rhode | 11 | 150 | 21.01 |
Gunnar Seemann | 12 | 212 | 48.50 |
Damien Sanchez-Quintana | 13 | 19 | 2.58 |
Javier Saiz | 14 | 45 | 18.51 |
Reza Razavi | 15 | 929 | 94.25 |
Olaf Dössel | 16 | 264 | 56.10 |