Multidimensional spectral analysis of the ultrasonic radiofrequency signal for characterization of media

Ultrasonics. 2016 May:68:89-101. doi: 10.1016/j.ultras.2016.02.010. Epub 2016 Feb 16.

Abstract

The importance of the analysis of the radiofrequency signal is by now recognized in the field of tissue characterization via ultrasound. The RF signal contains a wealth of information and structural details that are usually lost in the B-Mode representation. The HyperSPACE (Hyper SPectral Analysis for Characterization in Echography) algorithm presented by the authors in previous papers for clinical applications is based on the radiofrequency ultrasonic signal. The present work describes the method in detail and evaluates its performance in a repeatable and standardized manner, by using two test objects: a commercial test object that simulates the human parenchyma, and a laboratory-made test object consisting of human blood at different dilution values. In particular, the sensitivity and specificity in discriminating different density levels were estimated. In addition, the robustness of the algorithm with respect to the signal-to-noise ratio was also evaluated.

Keywords: Quantitative ultrasound; Signal processing; Spectral analysis; Tissue characterization; Ultrasonic radiofrequency signal.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Blood
  • Humans
  • Signal-To-Noise Ratio
  • Spectrum Analysis / methods*
  • Ultrasonics*