Cardiac motion estimation using covariant derivatives and Helmholtz decomposition

A. Becciu, R. Duits, B.J Janssen, L.M.J. Florack, B.M. Haar Romeny, ter, H.C. Assen, van

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

4 Citations (Scopus)
1 Downloads (Pure)

Abstract

Quantification of cardiac function is important for the assessment of abnormalities and response to therapy. We present a method to reconstruct dense cardiac motion from sparse features in tagging MRI, decomposed into solenoidal and irrotational parts using multi-scale Helmholtz decomposition. Reconstruction is based on energy minimization using covariant derivatives exploiting prior knowledge about the motion field. The method is tested on cardiac motion images. Experiments on phantom data show that both covariant derivatives and multi-scale Helmholtz decomposition improve motion field reconstruction.
Original languageEnglish
Title of host publicationStatistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges
Subtitle of host publicationSecond International Workshop, STACOM 2011, Held in Conjunction with MICCAI 2011, Toronto, ON, Canada, September 22, 2011, Revised Selected Papers
EditorsO. Camara, E. Konukoglu, M. Pop, K. Rhode, M. Sermesant, A. Young
Place of PublicationBerlin
PublisherSpringer
Pages263-273
Number of pages11
ISBN (Electronic)978-3-642-28326-0
ISBN (Print)978-3-642-28325-3
DOIs
Publication statusPublished - 2012
Event2nd International Workshop on Statistical Atlases and Computational Models of the Heart (STACOM 2011) - Toronto, Canada
Duration: 22 Sept 201122 Sept 2011
Conference number: 2

Publication series

NameLecture Notes in Computer Science (LNCS)
Volume7085
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference2nd International Workshop on Statistical Atlases and Computational Models of the Heart (STACOM 2011)
Abbreviated titleSTACOM 2011
Country/TerritoryCanada
CityToronto
Period22/09/1122/09/11
OtherWorkshop held in conjunction with the 14th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2011)

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