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MRI-based heart and torso personalization for computer modeling and simulation of cardiac electrophysiology

Abstract:

In the last decade, electrophysiological models for in-silico simulations of cardiac electrophysiology have gained much attention in the research field. However, to translate them to clinical uses, the models need personalization based on recordings from the patient. In this work, we explore methodologies for the patient-specific personalization of torso and heart geometric models based on standard clinical cardiac magnetic resonance acquisitions to enable simulations. The inclusion of the to...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1007/978-3-319-67552-7_8

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Oxford college:
St Catherine's College
Role:
Author
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Institution:
University of Oxford
Division:
MPLS Division
Department:
Computer Science
Role:
Author
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Institution:
University of Oxford
Division:
MPLS Division
Department:
Engineering Science
Role:
Author
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Institution:
University of Oxford
Division:
Medical Sciences Division
Department:
RDM; RDM Cardiovascular Medicine
Role:
Author
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Funding agency for:
Zacur, E
Grant:
655020- DTI4micro-MSCA-IF-EF-ST
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Funding agency for:
Minchole, A
Grant:
Senior Research Fellowship in Basic Biomedical Sciences to BR
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Funding agency for:
Villard, B
Grant:
Digital Economy Programme grant number EP/G036861/1
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Funding agency for:
Ariga, R
Grant:
Clinical Research Training Fellowship
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Funding agency for:
Rodriguez, B
Grant:
Senior Research Fellowship in Basic Biomedical Sciences
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Publisher:
Springer, Cham Publisher's website
Journal:
BIVPCS 2017, POCUS 2017: Imaging for Patient-Customized Simulations and Systems for Point-of-Care Ultrasound Journal website
Volume:
10549
Pages:
61-70
Series:
Lecture Notes in Computer Science
Host title:
BIVPCS 2017, POCUS 2017: Imaging for Patient-Customized Simulations and Systems for Point-of-Care Ultrasound
Publication date:
2017-09-08
Acceptance date:
2017-03-10
DOI:
ISSN:
0302-9743
Source identifiers:
734521
ISBN:
9783319675510
Pubs id:
pubs:734521
UUID:
uuid:5e4f4d46-9531-46c4-a5d0-6e729c587a58
Local pid:
pubs:734521
Deposit date:
2018-01-30

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