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Automatic left ventricle detection in echocardiographic images for deformable contour initialization

Conference Paper


Abstract


  • The accurate left ventricular boundary detection in echocardiographic images allow cardiologists to study and assess cardiomyopathy in patients. Due to the tedious and time consuming manner of manually tracing the borders, deformable models are generally used for left ventricle segmentations. However, most deformable models require a good initialization, which is usually outlined manually by the user. In this paper, we propose an automated left ventricle detection method for two-dimensional echocardiographic images that could serve as an initialization for deformable models. The proposed approach consists of pre-processing and post-processing stages, coupled with the watershed segmentation. The pre-processing stage enhances the overall contrast and reduces speckle noise, whereas the post-processing enhances the segmented region and avoids the papillary muscles. The performance of the proposed method is evaluated on real data. Experimental results show that it is suitable for automatic contour initialization since no prior assumptions nor human interventions are required. Besides, the computational time taken is also lower compared to an existing method.

Authors


  •   Seng, C H. (external author)
  •   Demirli, Ramazan (external author)
  •   Amin, Moeness G. (external author)
  •   Seachrist, Jason L. (external author)
  •   Bouzerdoum, Salim

Publication Date


  • 2011

Citation


  • C. H. Seng, R. Demirli, M. G. Amin, J. Seachrist & A. Bouzerdoum, "Automatic left ventricle detection in echocardiographic images for deformable contour initialization," in 33rd Annual International Conference of the IEEE EMBS, 2011, pp. 7215-7218.

Scopus Eid


  • 2-s2.0-84055223924

Ro Metadata Url


  • http://ro.uow.edu.au/infopapers/1508

Has Global Citation Frequency


Start Page


  • 7215

End Page


  • 7218

Place Of Publication


  • USA

Abstract


  • The accurate left ventricular boundary detection in echocardiographic images allow cardiologists to study and assess cardiomyopathy in patients. Due to the tedious and time consuming manner of manually tracing the borders, deformable models are generally used for left ventricle segmentations. However, most deformable models require a good initialization, which is usually outlined manually by the user. In this paper, we propose an automated left ventricle detection method for two-dimensional echocardiographic images that could serve as an initialization for deformable models. The proposed approach consists of pre-processing and post-processing stages, coupled with the watershed segmentation. The pre-processing stage enhances the overall contrast and reduces speckle noise, whereas the post-processing enhances the segmented region and avoids the papillary muscles. The performance of the proposed method is evaluated on real data. Experimental results show that it is suitable for automatic contour initialization since no prior assumptions nor human interventions are required. Besides, the computational time taken is also lower compared to an existing method.

Authors


  •   Seng, C H. (external author)
  •   Demirli, Ramazan (external author)
  •   Amin, Moeness G. (external author)
  •   Seachrist, Jason L. (external author)
  •   Bouzerdoum, Salim

Publication Date


  • 2011

Citation


  • C. H. Seng, R. Demirli, M. G. Amin, J. Seachrist & A. Bouzerdoum, "Automatic left ventricle detection in echocardiographic images for deformable contour initialization," in 33rd Annual International Conference of the IEEE EMBS, 2011, pp. 7215-7218.

Scopus Eid


  • 2-s2.0-84055223924

Ro Metadata Url


  • http://ro.uow.edu.au/infopapers/1508

Has Global Citation Frequency


Start Page


  • 7215

End Page


  • 7218

Place Of Publication


  • USA