Mean scatterer spacing estimation using multi-taper coherence

Nicholas Rubert, Tomy Varghese

Research output: Contribution to journalArticlepeer-review

17 Scopus citations


It has been hypothesized that estimates of mean scatterer spacing are useful indicators for pathological changes to the liver. A commonly employed estimator of the mean scatterer spacing is the location of the maximum of the collapsed average of coherence of the ultrasound radio-frequency signal. To date, in ultrasound, estimators for this quantity have been calculated with a single taper. Using frequency-domain Monte Carlo simulations, we demonstrate that multi-taper estimates of coherence are superior to single-taper estimates for predicting mean scatterer spacing. Scattering distributions were modeled with Gamma-distributed scatterers for fractional standard deviations in scatterer spacings of 5, 10, and 15% at a mean scatterer spacing of 1 mm. Additionally, we demonstrate that we can distinguish between ablated liver tissue and unablated liver tissue based on signal coherence. We find that, on the average, signal coherence is elevated in the liver relative to signal coherence of received echoes from thermally ablated tissue. Additionally, our analysis indicates that a tissue classifier utilizing the multi-taper estimate of coherence has the potential to distinguish between ablated and unablated tissue types better than a single-taper estimate of coherence. For a gate length of 5 mm, we achieved an error rate of only 8.7% when sorting 23 ablated and 23 unablated regions of interest (ROIs) into classes based on multi-taper calculations of coherence.

Original languageEnglish (US)
Article number6521056
Pages (from-to)1061-1073
Number of pages13
JournalIEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control
Issue number6
StatePublished - 2013

ASJC Scopus subject areas

  • Instrumentation
  • Electrical and Electronic Engineering
  • Acoustics and Ultrasonics


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