Applying a level set method for resolving physiologic motions in free-breathing and non-gated cardiac MRI

Ilyas Uyanik, Peggy Lindner, Panagiotis Tsiamyrtzis, Dipan Shah, Nikolaos V. Tsekos, Ioannis T. Pavlidis

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

3 Scopus citations

Abstract

In cardiac MRI, ECG triggering is used or patients are required to hold their breath, to alleviate motion artifacts and deterioration of image quality. However, ECG signal quality is often suboptimal and patients may not be able to adequately hold their breath. Alternative solutions for tracking breathing and cardiac beating can open the way for robust free-breathing and ECG-less cardiac MRI. Herein, we present a novel approach that isolates the effect of breathing, as well as computes both the breathing and cardiac beating waveforms directly from real-time MRI sequences. It turns a challenge into an opportunity to guide the reconstruction of high temporal resolution images. The proposed method is based on a level-set method to segment the left ventricle from a real-time MR sequence collected with free breathing and without ECG triggering. The algorithm extracts an evolving surface area, which captures the heart's systolic contraction and diastolic expansion in real-time. The computed time series of the heart's dynamic area is subjected to wavelet analysis, where the breathing and pulsation components are separated. The method was investigated on 12 real-time cardiac MRI acquisitions. We demonstrate that the left ventricular area, as computed by the level set method, produces breathing and cardiac waveforms similar with those extracted by cardiac MR experts (ground-truth). This proof-of-concept work demonstrates the capabilities of the proposed methodology paving the way for incorporation into real-time or retrospective reconstruction of high resolution cardiac MR.

Original languageEnglish (US)
Title of host publicationFunctional Imaging and Modeling of the Heart - 7th International Conference, FIMH 2013, Proceedings
Pages466-473
Number of pages8
DOIs
StatePublished - 2013
Event7th International Conference on Functional Imaging and Modeling of the Heart, FIMH 2013 - London, United Kingdom
Duration: Jun 20 2013Jun 22 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7945 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other7th International Conference on Functional Imaging and Modeling of the Heart, FIMH 2013
CountryUnited Kingdom
CityLondon
Period6/20/136/22/13

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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