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Efficient Two-Pass 3-D Speckle Tracking for Ultrasound Imaging.
Jeng, Geng-Shi; Zontak, Maria; Parajuli, Nripesh; Lu, Allen; Ta, Kevinminh; Sinusas, Albert J; Duncan, James S; O'Donnell, Matthew.
Afiliação
  • Jeng GS; Department of Bioengineering, University of Washington, Seattle, WA 98195 USA.
  • Zontak M; College of Computer and Information Science, Northeastern University, Seattle, WA 98109 USA.
  • Parajuli N; Department of Electrical Engineering, Yale University, New Haven, CT 06520 USA.
  • Lu A; Department of Biomedical Engineering, Yale University, New Haven, CT 06520 USA.
  • Ta K; Department of Biomedical Engineering, Yale University, New Haven, CT 06520 USA.
  • Sinusas AJ; Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT 06520 USA.
  • Duncan JS; Department of Electrical Engineering, Yale University, New Haven, CT 06520 USA.
  • O'Donnell M; Department of Biomedical Engineering, Yale University, New Haven, CT 06520 USA.
IEEE Access ; 6: 17415-17428, 2018.
Article em En | MEDLINE | ID: mdl-30740286
Speckle tracking based on block matching is the most common method for multi-dimensional motion estimation in ultrasound elasticity imaging. Extension of two-dimensional (2-D) methods to three dimensions (3-D) has been problematic because of the large computational load of 3-D tracking, as well as performance issues related to the low frame (volume) rates of 3-D images. To address both of these problems, we have developed an efficient two-pass tracking method suited to cardiac elasticity imaging. PatchMatch, originally developed for image editing, has been adapted for ultrasound to provide first-pass displacement estimates. Second-pass estimation uses conventional block matching within a much smaller search region. 3-D displacements are then obtained using correlation filtering previously shown to be effective against speckle decorrelation. Both simulated and in vivo canine cardiac results demonstrate that the proposed two-pass method reduces computational cost compared to conventional 3-D exhaustive search by a factor of 10. Moreover, it outperforms one-pass tracking by a factor of about 3 in terms of root-mean-square error relative to available ground-truth displacements.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2018 Tipo de documento: Article