Order selection criteria for detecting mean scatterer spacings with the ar model

Tomy Varghese, Kevin D. Donohue, Vlad I. Genis, Ethan J. Halpern

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


This paper examines the detection of regular scatterer spacing From backscattered ultrasound using the autoregressive (AR) ccpstrum. Monte Carlo simulations present a relationship between the probability of detection and the AR model order. An example using liver tissue data supports the observations made in the simulation.

Original languageEnglish
Pages (from-to)979-984
Number of pages6
JournalIEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control
Issue number5
StatePublished - 1996

Bibliographical note

Funding Information:
Mean scatterer spacing has been estimated from intensity scans using the autocorrelation function [7], [8], and from RF scans using cepstral [4]-[6] and spectral correlation [9]-[ 11 1 techniques. Cepstral methods use the inverse Fourier transform of the logarithm of the power spectrum to separate the slow variations in the magnitude spectrum due to the system response from the rapid variation due to the periodicities of the scatterer spacings. After windowing out from the cepstrum the system effects that occur within the resolution is based on work supported in part by the National Cancer Institute and the National Institutes of Health Grant Pol-CA52823-05. T. Varghese is with the Ultrasonics Laboratory, Department of Radiology, University of Texas Medical School at Houston, Houston, TX 77054 USA. K. D. Donohue is with the Department of Electrical Engineering, University of Kentucky, Lexington, KY 40503 USA (e-mail: donohue@engr.uky.edu). V. I. Genis is with the Biomedical Engineering and Science Institute, Drexel University, Philadelphia. PA 19104 USA, E. J. Halpern is with the Division of Ultrasound, Thomas Jefferson University Hospital, Philadelphia, PA 19 107 USA. Publisher Item Identifier S 0885-3010(96)06320-4.

ASJC Scopus subject areas

  • Instrumentation
  • Acoustics and Ultrasonics
  • Electrical and Electronic Engineering


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