Fully Automated and Robust Tracking of Transient Waves in Structured Anatomies Using Dynamic Programming

Zeynettin Akkus, Mahdi Bayat, Mathew Cheong, Kumar Viksit, Bradley J. Erickson, Azra Alizad, Mostafa Fatemi

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Tissue stiffness is often linked to underlying pathology and can be quantified by measuring the mechanical transient transverse wave speed (TWS) within the medium. Time-of-flight methods based on correlation of the transient signals or tracking of peaks have been used to quantify the TWS from displacement maps obtained with ultrasound pulse-echo techniques. However, it is challenging to apply these methods to in vivo data because of tissue inhomogeneity, noise and artifacts that produce outliers. In this study, we introduce a robust and fully automated method based on dynamic programming to estimate TWS in tissues with known geometries. The method is validated using ultrasound bladder vibrometry data from an in vivo study. We compared the results of our method with those of time-of-flight techniques. Our method performs better than time-of-flight techniques. In conclusion, we present a robust and accurate TWS detection method that overcomes the difficulties of time-of-flight methods.

Original languageEnglish (US)
Pages (from-to)2504-2512
Number of pages9
JournalUltrasound in Medicine and Biology
Volume42
Issue number10
DOIs
StatePublished - 2016

Keywords

  • Bladder
  • Dynamic programming
  • Time-of-flight
  • Ultrasound vibrometery
  • Wall stiffness
  • Wave tracking

ASJC Scopus subject areas

  • Biophysics
  • Radiological and Ultrasound Technology
  • Acoustics and Ultrasonics

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