Dr MARCO IGLESIAS HERNANDEZ Marco.Iglesias@nottingham.ac.uk
ASSOCIATE PROFESSOR
Ensemble Kalman inversion for magnetic resonance elastography.
Iglesias, Marco; McGrath, Deirdre M.; Tretyakov, M. V.; Francis, Susan T
Authors
Deirdre M. McGrath
Professor MIKHAIL TRETYAKOV Michael.Tretyakov@nottingham.ac.uk
PROFESSOR OF MATHEMATICS
Professor SUSAN FRANCIS susan.francis@nottingham.ac.uk
PROFESSOR OF PHYSICS
Abstract
Magnetic Resonance Elastography (MRE) is an MRI-based diagnostic method for measuring mechanical properties of biological tissues. MRE measurements are processed by an inversion algorithm to produce a map of the biomechanical properties. In this paper a new and powerful method (Ensemble Kalman Inversion with Level Sets (EKI)) of MRE inversion is proposed and tested. The method has critical advantages: material property variation at disease boundaries can be accurately identified, and uncertainty of the reconstructed material properties can be evaluated by consequence of the probabilistic nature of the method. EKI is tested in 2D and 3D experiments with synthetic MRE data of the human kidney. It is demonstrated that the proposed inversion method is accurate and fast.
Citation
Iglesias, M., McGrath, D. M., Tretyakov, M. V., & Francis, S. T. (2022). Ensemble Kalman inversion for magnetic resonance elastography. Physics in Medicine and Biology, 67(23), Article 235003. https://doi.org/10.1088/1361-6560/ac9fa1
Journal Article Type | Article |
---|---|
Acceptance Date | Nov 1, 2022 |
Online Publication Date | Nov 2, 2022 |
Publication Date | Dec 7, 2022 |
Deposit Date | Nov 11, 2022 |
Publicly Available Date | Nov 17, 2022 |
Journal | Physics in Medicine and Biology |
Print ISSN | 0031-9155 |
Electronic ISSN | 1361-6560 |
Publisher | IOP Publishing |
Peer Reviewed | Peer Reviewed |
Volume | 67 |
Issue | 23 |
Article Number | 235003 |
DOI | https://doi.org/10.1088/1361-6560/ac9fa1 |
Keywords | Radiology, Nuclear Medicine and imaging; Radiological and Ultrasound Technology |
Public URL | https://nottingham-repository.worktribe.com/output/13181942 |
Publisher URL | https://iopscience.iop.org/article/10.1088/1361-6560/ac9fa1 |
Files
Iglesias_2022_Phys._Med._Biol._67_235003
(3 Mb)
PDF
Publisher Licence URL
https://creativecommons.org/licenses/by/4.0/
You might also like
Real-time Bayesian inversion in resin transfer moulding using neural surrogates
(2024)
Journal Article
Ensemble Kalman inversion of induced polarization data
(2024)
Journal Article
On a Dynamic Variant of the Iteratively Regularized Gauss–Newton Method with Sequential Data
(2023)
Journal Article
Downloadable Citations
About Repository@Nottingham
Administrator e-mail: discovery-access-systems@nottingham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search