Autoregressive spectral estimation in ultrasonic scatterer size imaging

Pawan Chaturvedi, Michael F. Insana

Research output: Contribution to journalArticlepeer-review

Abstract

An autoregressive (AR) spectral estimation method was considered for the purpose of estimating scatterer size images. The variance and bias of the resulting estimates were compared with those using classical FFT periodograms for a range of input signal-to-noise ratios and echo-signal durations corresponding to various C-scan image slice thicknesses. The AR approach was found to produce images of significantly higher quality for noisy data and when thin slices were required. Several images reconstructed with the two techniques are presented to demonstrate difference in visual quality Task- specific guidelines for empirical selection of the AR model order are also proposed.

Original languageEnglish (US)
Pages (from-to)10-24
Number of pages15
JournalUltrasonic Imaging
Volume18
Issue number1
DOIs
StatePublished - 1996
Externally publishedYes

Keywords

  • Autoregressive models
  • parametric imaging
  • periodogram
  • spectral estimation
  • tissue characterization

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Acoustics and Ultrasonics

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