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Journal article

LV segmentation through the analysis of radio frequency ultrasonic images.

Yan P, Jia C, Sinusas A, Thiele K, O'Donnell M, Duncan J...(+6 more)

Information processing in medical imaging : proceedings of the ... conference, vol. 20 (2007) pp. 233-44

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LV segmentation is often an important part of many automated cardiac diagnosis strategies. However, the segmentation of echocardiograms is a difficult task because of poor image quality. In echocardiography, we note that radio-frequency (RF) signal is a rich source of information about the moving LV as well. In this paper, first, we will investigate currently used, important RF derived parameters: integrated backscatter coefficient (IBS), mean central frequency (MCF) and the maximum correlation coefficients (MCC) from speckle tracking. Second, we will develop a new segmentation algorithm for the segmentation of the LV boundary, which can avoid local minima and leaking through uncompleted boundary. Segmentations are carried out on the RF signal acquired from a Sonos7500 ultrasound system. The results are validated by comparing to manual segmentation results.

Author-supplied keywords

  • Algorithms
  • Artificial Intelligence
  • Automated
  • Automated: methods
  • Computer-Assisted
  • Computer-Assisted: methods
  • Echocardiography
  • Echocardiography: methods
  • Heart Ventricles
  • Heart Ventricles: ultrasonography
  • Humans
  • Image Enhancement
  • Image Enhancement: methods
  • Image Interpretation
  • Pattern Recognition
  • Radio Waves
  • Radio Waves: diagnostic use
  • Reproducibility of Results
  • Sensitivity and Specificity

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