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30 May 2001 Estimating backscatter spectra after deconvolution with Kalman smoothing
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In quantitative tissue characterization. Obtaining processed ultrasonic echoes with a direct relationship to local tissue response (backscatter spectrum) and that are free from systemic depth-dependent effects, such as diffraction, is essential. In general practice today, these unwanted distortions are eliminated by dividing short time power spectra. However, this method has its drawbacks; noise is not taken into account, and shorter time gates lead to an increasing bias within the relative spectra. To overcome these methodological issues, I propose a different approach as follows. Entire deconvolved A-scans are estimated by a Kalman smoothing deconvolution algorithm. These then serve as a basis for estimating the relative backscatter spectra. In addition, due to the principle of the deconvolution algorithm, it is possible to suppress additive noise to some degree. To examine the properties of the method proposed, this paper presents an analytical expression for the power spectrum of the deconvolved signals obtained by Kalman Smoothing. This result is then compared to the expectations of relative short time power spectra. Simulations demonstrate the behavior of the deconvolution method in a non-stationary environment.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Armin I. Guenter "Estimating backscatter spectra after deconvolution with Kalman smoothing", Proc. SPIE 4325, Medical Imaging 2001: Ultrasonic Imaging and Signal Processing, (30 May 2001);

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