Segmentation of 3D cardiac ultrasound images using correlation of radio frequency data

M. M. Nillesen, R. G.P. Lopata, I. H. Gerrits, H. J. Huisman, J. M. Thijssen, L. Kapusta, C. L. De Korte

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

2 Scopus citations

Abstract

Semi-automatic segmentation of the heart muscle in 3D echographic images may substantially support clinical diagnosis of heart disease. Especially in children with congenital heart disease, segmentation should be based on the echo features solely since a priori knowledge on the shape of the heart cannot be used. Segmentation of echocardiographic images is challenging because of the low echogenicity of the myocardium in some regions. High resolution information derived from radio frequency (rf) ultrasound data might be a useful additional feature in these regions. A semi-3D technique was used to determine maximum temporal cross-correlation values from the rf-data. To segment the endocardial surface, maximum cross-correlation values were used as additional external force in a deformable model approach and were tested against and combined with adaptive filtered, demodulated rf-data. The method was tested on pediatric full volume images (Philips, iE33) and evaluated by comparison with contours obtained from manual segmentation.

Original languageEnglish
Title of host publicationProceedings - 2009 IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro, ISBI 2009
Pages522-525
Number of pages4
DOIs
StatePublished - 2009
Externally publishedYes
Event2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009 - Boston, MA, United States
Duration: 28 Jun 20091 Jul 2009

Publication series

NameProceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009

Conference

Conference2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009
Country/TerritoryUnited States
CityBoston, MA
Period28/06/091/07/09

Keywords

  • 3D echocardiography
  • Deformable model
  • Image segmentation
  • Temporal cross-correlation
  • Ultrasound

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