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Conference Paper/Proceeding/Abstract 765 views 194 downloads

Manifold Modeling of the Beating Heart Motion

Paul Stroe, Xianghua Xie Orcid Logo, Adeline Paiement

Communications in Computer and Information Science, Volume: 894, Pages: 229 - 238

Swansea University Authors: Xianghua Xie Orcid Logo, Adeline Paiement

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DOI (Published version): 10.1007/978-3-319-95921-4_22

Abstract

Modeling the heart motion has important applications for diagnosis and intervention. We present a new method for modeling the deformation of the myocardium in the cardiac cycle. Our approach is based on manifold learning to build a representation of shape variation across time. We experiment with va...

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Published in: Communications in Computer and Information Science
ISBN: 9783319959207 9783319959214
ISSN: 1865-0929 1865-0937
Published: Cham Springer International Publishing 2018
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URI: https://cronfa.swan.ac.uk/Record/cronfa39317
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first_indexed 2018-04-05T13:37:15Z
last_indexed 2022-06-17T02:55:27Z
id cronfa39317
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spelling 2022-06-16T16:06:09.5496003 v2 39317 2018-04-05 Manifold Modeling of the Beating Heart Motion b334d40963c7a2f435f06d2c26c74e11 0000-0002-2701-8660 Xianghua Xie Xianghua Xie true false f50adf4186d930e3a2a0f9a6d643cf53 Adeline Paiement Adeline Paiement true false 2018-04-05 SCS Modeling the heart motion has important applications for diagnosis and intervention. We present a new method for modeling the deformation of the myocardium in the cardiac cycle. Our approach is based on manifold learning to build a representation of shape variation across time. We experiment with various manifold types to identify the best manifold method, and with real patient data extracted from cine MRIs. We obtain a representation, common to all subjects, that can discriminate cardiac cycle phases and heart function types. Conference Paper/Proceeding/Abstract Communications in Computer and Information Science 894 229 238 Springer International Publishing Cham 9783319959207 9783319959214 1865-0929 1865-0937 Beating Heart Motion; Manifold Model; Manifold Types; Manifold Learning Methods; Cardiac Cycle Phase 21 8 2018 2018-08-21 10.1007/978-3-319-95921-4_22 COLLEGE NANME Computer Science COLLEGE CODE SCS Swansea University 2022-06-16T16:06:09.5496003 2018-04-05T09:43:54.0028052 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Paul Stroe 1 Xianghua Xie 0000-0002-2701-8660 2 Adeline Paiement 3 0039317-05042018100509.pdf manifold-modeling-beating.pdf 2018-04-05T10:05:09.4330000 Output 1549153 application/pdf Accepted Manuscript true 2019-08-21T00:00:00.0000000 true eng
title Manifold Modeling of the Beating Heart Motion
spellingShingle Manifold Modeling of the Beating Heart Motion
Xianghua Xie
Adeline Paiement
title_short Manifold Modeling of the Beating Heart Motion
title_full Manifold Modeling of the Beating Heart Motion
title_fullStr Manifold Modeling of the Beating Heart Motion
title_full_unstemmed Manifold Modeling of the Beating Heart Motion
title_sort Manifold Modeling of the Beating Heart Motion
author_id_str_mv b334d40963c7a2f435f06d2c26c74e11
f50adf4186d930e3a2a0f9a6d643cf53
author_id_fullname_str_mv b334d40963c7a2f435f06d2c26c74e11_***_Xianghua Xie
f50adf4186d930e3a2a0f9a6d643cf53_***_Adeline Paiement
author Xianghua Xie
Adeline Paiement
author2 Paul Stroe
Xianghua Xie
Adeline Paiement
format Conference Paper/Proceeding/Abstract
container_title Communications in Computer and Information Science
container_volume 894
container_start_page 229
publishDate 2018
institution Swansea University
isbn 9783319959207
9783319959214
issn 1865-0929
1865-0937
doi_str_mv 10.1007/978-3-319-95921-4_22
publisher Springer International Publishing
college_str Faculty of Science and Engineering
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hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science
document_store_str 1
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description Modeling the heart motion has important applications for diagnosis and intervention. We present a new method for modeling the deformation of the myocardium in the cardiac cycle. Our approach is based on manifold learning to build a representation of shape variation across time. We experiment with various manifold types to identify the best manifold method, and with real patient data extracted from cine MRIs. We obtain a representation, common to all subjects, that can discriminate cardiac cycle phases and heart function types.
published_date 2018-08-21T03:49:55Z
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score 10.998002

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