No Cover Image

Conference Paper/Proceeding/Abstract 1175 views 309 downloads

Manifold Modeling of the Beating Heart Motion

Paul Stroe, Xianghua Xie Orcid Logo, Adeline Paiement Orcid Logo

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

Swansea University Authors: Xianghua Xie Orcid Logo, Adeline Paiement Orcid Logo

Check full text

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...

Full description

Published in: Communications in Computer and Information Science
ISBN: 9783319959207 9783319959214
ISSN: 1865-0929 1865-0937
Published: Cham Springer International Publishing 2018
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa39317
first_indexed 2018-04-05T13:37:15Z
last_indexed 2022-06-17T02:55:27Z
id cronfa39317
recordtype SURis
fullrecord <?xml version="1.0"?><rfc1807><datestamp>2022-06-16T16:06:09.5496003</datestamp><bib-version>v2</bib-version><id>39317</id><entry>2018-04-05</entry><title>Manifold Modeling of the Beating Heart Motion</title><swanseaauthors><author><sid>b334d40963c7a2f435f06d2c26c74e11</sid><ORCID>0000-0002-2701-8660</ORCID><firstname>Xianghua</firstname><surname>Xie</surname><name>Xianghua Xie</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>f50adf4186d930e3a2a0f9a6d643cf53</sid><ORCID>0000-0001-5114-1514</ORCID><firstname>Adeline</firstname><surname>Paiement</surname><name>Adeline Paiement</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2018-04-05</date><deptcode>MACS</deptcode><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 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.</abstract><type>Conference Paper/Proceeding/Abstract</type><journal>Communications in Computer and Information Science</journal><volume>894</volume><journalNumber/><paginationStart>229</paginationStart><paginationEnd>238</paginationEnd><publisher>Springer International Publishing</publisher><placeOfPublication>Cham</placeOfPublication><isbnPrint>9783319959207</isbnPrint><isbnElectronic>9783319959214</isbnElectronic><issnPrint>1865-0929</issnPrint><issnElectronic>1865-0937</issnElectronic><keywords>Beating Heart Motion; Manifold Model; Manifold Types; Manifold Learning Methods; Cardiac Cycle Phase</keywords><publishedDay>21</publishedDay><publishedMonth>8</publishedMonth><publishedYear>2018</publishedYear><publishedDate>2018-08-21</publishedDate><doi>10.1007/978-3-319-95921-4_22</doi><url/><notes/><college>COLLEGE NANME</college><department>Mathematics and Computer Science School</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>MACS</DepartmentCode><institution>Swansea University</institution><apcterm/><lastEdited>2022-06-16T16:06:09.5496003</lastEdited><Created>2018-04-05T09:43:54.0028052</Created><path><level id="1">Faculty of Science and Engineering</level><level id="2">School of Mathematics and Computer Science - Computer Science</level></path><authors><author><firstname>Paul</firstname><surname>Stroe</surname><order>1</order></author><author><firstname>Xianghua</firstname><surname>Xie</surname><orcid>0000-0002-2701-8660</orcid><order>2</order></author><author><firstname>Adeline</firstname><surname>Paiement</surname><orcid>0000-0001-5114-1514</orcid><order>3</order></author></authors><documents><document><filename>0039317-05042018100509.pdf</filename><originalFilename>manifold-modeling-beating.pdf</originalFilename><uploaded>2018-04-05T10:05:09.4330000</uploaded><type>Output</type><contentLength>1549153</contentLength><contentType>application/pdf</contentType><version>Accepted Manuscript</version><cronfaStatus>true</cronfaStatus><embargoDate>2019-08-21T00:00:00.0000000</embargoDate><copyrightCorrect>true</copyrightCorrect><language>eng</language></document></documents><OutputDurs/></rfc1807>
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 0000-0001-5114-1514 Adeline Paiement Adeline Paiement true false 2018-04-05 MACS 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 Mathematics and Computer Science School COLLEGE CODE MACS 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 0000-0001-5114-1514 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
hierarchytype
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
active_str 0
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 2018-08-21T04:20:06Z
_version_ 1851093582365065216
score 11.089386

Similar Items