Improved Harmonic Phase (HARP) method for motion tracking a tagged cardiac MR images

Ayman M. Khalifa, Abou Bakr M. Youssef, Nael F. Osman

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

21 Scopus citations

Abstract

The diagnosis of cardiovascular disease requires precise assessment of both morphology and function of the heart. Currently, magnetic resonance imaging (MRI) provides a useful tool for accurate and reproducible assessment of regional function of the left ventricle noninvasively. MR tagging produces images of the heart that can be analyzed using harmonic phase (HARP) method to describe the regional function of the heart. In order to calculate regional function, a circular mesh is manually built at a specific timeframe, after which the points of such mesh are tracked using the HARP technique. The tracking is not perfect and some individual points on the mesh could fail in tracking. In this work, a new method is presented to improve the tracking by combining HARP with active contour methods. This modified HARP technique is more robust than the previous HARP technique.

Original languageEnglish (US)
Title of host publicationProceedings of the 2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4298-4301
Number of pages4
ISBN (Print)0780387406, 9780780387409
DOIs
StatePublished - 2005
Event2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005 - Shanghai, China
Duration: Sep 1 2005Sep 4 2005

Publication series

NameAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume7 VOLS
ISSN (Print)0589-1019

Other

Other2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005
Country/TerritoryChina
CityShanghai
Period9/1/059/4/05

Keywords

  • Active contour model
  • MR tagging
  • Motion tracking

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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