Tools
Tools
Chinchapatnam, P. P., Rhode, K. S., King, A., Gao, G., Ma, Y. 
ORCID: https://orcid.org/0000-0001-5770-5843, Schaeffter, T., Hawkes, David J., Razavi, R.S., Hill, Derek L.G., Arridge, S. and Sermesant, Maxime
(2007)
Anisotropic wave propagation and apparent conductivity estimation in a fast electrophysiological model: Application to XMR interventional imaging.
In:
Medical Image Computing and Computer-Assisted Intervention.
Lecture Notes in Computer Science
.
Springer, 575–583.
ISBN 978-3-540-75756-6
Abstract
Cardiac arrhythmias are increasingly being treated using ablation procedures. Development of fast electrophysiological models and estimation of parameters related to conduction pathologies can aid in the investigation of better treatment strategies during Radio-frequency ablations. We present a fast electrophysiological model incorporating anisotropy of the cardiac tissue. A global-local estimation procedure is also outlined to estimate a hidden parameter (apparent electrical conductivity) present in the model. The proposed model is tested on synthetic and real data derived using XMR imaging. We demonstrate a qualitative match between the estimated conductivity parameter and possible pathology locations. This approach opens up possibilities to directly integrate modelling in the intervention room.
| Item Type: | Book Section |
|---|---|
| Faculty \ School: | Faculty of Science > School of Computing Sciences |
| UEA Research Groups: | Faculty of Science > Research Groups > Norwich Epidemiology Centre Faculty of Medicine and Health Sciences > Research Groups > Norwich Epidemiology Centre Faculty of Science > Research Groups > Data Science and AI |
| Related URLs: | |
| Depositing User: | LivePure Connector |
| Date Deposited: | 05 Jan 2023 10:30 |
| Last Modified: | 10 Dec 2024 01:13 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/90399 |
| DOI: | 10.1007/978-3-540-75757-3_70 |
Actions (login required)
 |
View Item |