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A theoretical analysis was performed to describe statistical characteristics of calibrated spectral parameters used for ultrasonic tissue evaluation in the prostate and liver. The analysis assumes that radiofrequency (rf) echo signals exhibit Gaussian statistics. It derives the probability density function (pdf) of spectral parameters that are computed using sliding-window analysis techniques. The analysis relates the standard deviations of linear-regression spectral-parameter estimates to system and analysis parameters including bandwidth, center frequency, and the length of the sliding analysis window. The analysis also derives the pdf for mid-band fit parameter images. Theoretical results are found to agree well with clinical data from homogeneous segments in liver and prostate. The results offer a basis for evaluating spectral-estimator precision and for conducting future studies of lesion detectability based on spectral features.
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Lizzi et al. (1997) studied this question.
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