Quantitative analysis of noise influence on the detection of scatterer concentration by Nakagami parameter

Po Hsiang Tsui, Shyh-Hau Wang, Chih-Chung Huang, Chun Yi Chiu

Research output: Contribution to journalArticlepeer-review

23 Citations (Scopus)

Abstract

The Nakagami statistical parameter has been demonstrated to be capable of detecting the variation of scatterer concentration in a biological tissue. The accuracy and sensitivity of the Nakagami parameter would be varied by the quality of ultrasonic backscattered signals, which is further affected by noise interference. For this reason, the experimental measurements and two-dimensional computer simulations were carried out to explore the effect of noise on the estimation of the Nakagami parameter as a function of scatterer concentration. The noise of the practical measurement system was acquired and subsequently its probability density function (PDF) and the Nakagami parameter were calculated. The incorporated simulation study was performed to evaluate the performances of the Nakagami parameter estimated from ultrasonic backscattered signals associated with different levels of signal-to-noise ratio (SNR) by adding simulated white noises with 5 MHz ultrasonic echoes corresponding to different scatterer concentrations. The obtained results showed that the envelope of white noise follows the Rayleigh distribution discernible by the calculated Nakagami parameter close to unity. Moreover, the sensitivity of Nakagami parameter to differentiate different scatterer concentrations decreased gradually corresponding to the decrease of SNR of backscattered signals. The SNR of backscattered signals was further suggested to be at least higher than 11 dB to affirm a satisfactory performance of the Nakagami parameter for characterizing the properties of biological tissues.

Original languageEnglish
Pages (from-to)45-51
Number of pages7
JournalJournal of Medical and Biological Engineering
Volume25
Issue number2
Publication statusPublished - 2005 Jun 1

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering

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