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Biventricular surface reconstruction from cine MRI contours using point completion networks

Abstract:

Many important cardiac biomarkers used in clinical practice describe cardiac anatomy and function in three dimensions (3D). However, common cardiac magnetic resonance imaging (MRI) protocols often only generate two-dimensional (2D) image slices of the underlying 3D anatomy and are susceptible to various types of motion artifacts causing slice misalignment. In this paper, we propose a deep learning method acting directly on point clouds to reconstruct a dense 3D biventricular heart model from ...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/ISBI48211.2021.9434040

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
RDM
Sub department:
RDM Cardiovascular Medicine
Role:
Author
ORCID:
0000-0001-8198-5128
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
ORCID:
0000-0001-8139-3480
Publisher:
Institute of Electrical and Electronics Engineers Publisher's website
Pages:
105-109
Host title:
2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI)
Publication date:
2021-05-25
Acceptance date:
2021-02-08
Event title:
IEEE ISBI 2021: International Symposium on Biomedical Imaging
Event location:
Virtual event
Event website:
https://biomedicalimaging.org/2021/
Event start date:
2021-04-13T00:00:00Z
Event end date:
2021-04-16T00:00:00Z
DOI:
EISBN:
9781665412469
ISBN:
9781665429474
Language:
English
Keywords:
Pubs id:
1171959
Local pid:
pubs:1171959
Deposit date:
2021-04-17

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