Real-time regularized ultrasound elastography

Hassan Rivaz, Emad M. Boctor, Michael A. Choti, Gregory D. Hager

Research output: Contribution to journalArticlepeer-review

156 Scopus citations


This paper introduces two real-time elastography techniques based on analytic minimization (AM) of regularized cost functions. The first method (1D AM) produces axial strain and integer lateral displacement, while the second method (2D AM) produces both axial and lateral strains. The cost functions incorporate similarity of radiofrequency (RF) data intensity and displacement continuity, making both AM methods robust to small decorrelations present throughout the image. We also exploit techniques from robust statistics to make the methods resistant to large local decorrelations. We further introduce Kalman filtering for calculating the strain field from the displacement field given by the AM methods. Simulation and phantom experiments show that both methods generate strain images with high SNR, CNR and resolution. Both methods work for strains as high as 10% and run in real-time. We also present in vivo patient trials of ablation monitoring. An implementation of the 2D AM method as well as phantom and clinical RF-data can be downloaded.

Original languageEnglish (US)
Article number5629442
Pages (from-to)928-945
Number of pages18
JournalIEEE Transactions on Medical Imaging
Issue number4
StatePublished - Apr 1 2011


  • Kalman filter
  • radio-frequency (RF) ablation
  • real-time ultrasound elastography
  • regulariation
  • robust estimation
  • two-dimensional (2D) strain

ASJC Scopus subject areas

  • Software
  • Radiological and Ultrasound Technology
  • Computer Science Applications
  • Electrical and Electronic Engineering


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