Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Preprint |
| Published: |
2022
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2207.14624 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866913694147936256 |
|---|---|
| author | Mackenzie, Jay Aodh Miller, Megan Jeanne Hill, Nicholas Olufsen, Mette |
| author_facet | Mackenzie, Jay Aodh Miller, Megan Jeanne Hill, Nicholas Olufsen, Mette |
| contents | Numerical simulations of real-world phenomena require a computational scheme and a computational domain. In the context of haemodynamics, the computational domain is the blood vessel network through which blood flows. Such networks contain millions of vessels that are joined in series and in parallel. It is computationally unfeasible to explicitly simulate blood flow throughout the network. From a single porcine left coronary arterial tree, we develop a data pipeline to obtain computational domains for haemodynamic simulations in the myocardium from a graph representing a partial coronary arterial tree. In addition, we develop a method to ascertain which subregions of the left-ventricular wall are more likely to be perfused via a given artery, using a comparison with the American Heart Association division of the left ventricle for validation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2207_14624 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | Post-processing of coronary and myocardial spatial data Mackenzie, Jay Aodh Miller, Megan Jeanne Hill, Nicholas Olufsen, Mette Discrete Mathematics Computer Vision and Pattern Recognition Numerical simulations of real-world phenomena require a computational scheme and a computational domain. In the context of haemodynamics, the computational domain is the blood vessel network through which blood flows. Such networks contain millions of vessels that are joined in series and in parallel. It is computationally unfeasible to explicitly simulate blood flow throughout the network. From a single porcine left coronary arterial tree, we develop a data pipeline to obtain computational domains for haemodynamic simulations in the myocardium from a graph representing a partial coronary arterial tree. In addition, we develop a method to ascertain which subregions of the left-ventricular wall are more likely to be perfused via a given artery, using a comparison with the American Heart Association division of the left ventricle for validation. |
| title | Post-processing of coronary and myocardial spatial data |
| topic | Discrete Mathematics Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2207.14624 |