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Automatic cardiac motion tracking using both untagged and 3D tagged MR images

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Haiyan Wang, Wenzhe Shi, Xiahai Zhuang, Simon Duckett, Kaipin Tung, Philip Edwards, Reza Razavi, Sebastien Ourselin, Daniel Rueckert

Original languageEnglish
Title of host publicationStatistical Atlases and Computational Models of the Heart
Subtitle of host publicationImaging and Modelling Challenges - Second International Workshop, STACOM 2011, Held in Conjunction with MICCAI 2011, Revised Selected Papers
Pages45-54
Number of pages10
DOIs
Publication statusPublished - 21 Mar 2012
Event2nd International Workshop on Statistical Atlases and Computational Models of the Heart: Imaging and Modelling Challenges, STACOM 2011, Held in Conjunction with MICCAI 2011 - Toronto, ON, Canada
Duration: 22 Sep 201122 Sep 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7085 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference2nd International Workshop on Statistical Atlases and Computational Models of the Heart: Imaging and Modelling Challenges, STACOM 2011, Held in Conjunction with MICCAI 2011
CountryCanada
CityToronto, ON
Period22/09/201122/09/2011

King's Authors

Abstract

We present a fully automatic framework for cardiac motion tracking based on non-rigid image registration for the analysis of myocardial motion using both untagged and 3D tagged MR images. We detect and track anatomical landmarks in the heart and combine this with intensity-based motion tracking to allow accurately model cardiac motion while significantly reduce the computational complexity. A collaborative similarity measure simultaneously computed in three LA views is employed to register a sequence of images taken during the cardiac cycle to a reference image taken at end-diastole. We then integrate a valve plane tracker into the framework which uses short-axis and long-axis untagged MR images as well as 3D tagged images to estimate a fully four-dimensional motion field of the left ventricle.

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