Incompressible cardiac motion estimation of the left ventricle using tagged MR images

Xiaofeng Liu, Khaled Z. Abd-Elmoniem, Jerry L. Prince

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

Abstract

Interpolation from sparse imaging data is typically required to achieve dense, three-dimensional quantification of left ventricular function. Although the heart muscle is known to be incompressible, this fact is ignored by most previous approaches that address this problem. In this paper, we present a method to reconstruct a dense representation of the three-dimensional, incompressible deformation of the left ventricle from tagged MR images acquired in both short-axis and long axis orientations. The approach applies a smoothing, divergence-free, vector spline to interpolate velocity fields at intermediate discrete times such that the collection of velocity fields integrate over time to match the observed displacement components. Through this process, the method yields a dense estimate of a displacement field that matches our observations and also corresponds to an incompressible motion.

Original languageEnglish (US)
Title of host publicationMedical Image Computing and Computer-Assisted Intervention - MICCAI2009 - 12th International Conference, Proceedings
Pages331-338
Number of pages8
EditionPART 2
DOIs
StatePublished - Dec 1 2009
Event12th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2009 - London, United Kingdom
Duration: Sep 20 2009Sep 24 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume5762 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other12th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2009
CountryUnited Kingdom
CityLondon
Period9/20/099/24/09

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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