title: Adaptive spectral doppler estimation.
abstract: In this paper, 2 adaptive spectral estimation techniques are analyzed for spectral Doppler ultrasound. The purpose is to minimize the observation window needed to estimate the spectrogram to provide a better temporal resolution and gain more flexibility when designing the data acquisition sequence. The methods can also provide better quality of the estimated power spectral density (PSD) of the blood signal. Adaptive spectral estimation techniques are known to provide good spectral resolution and contrast even when the observation window is very short. The 2 adaptive techniques are tested and compared with the averaged periodogram (Welch's method). The blood power spectral capon (BPC) method is based on a standard minimum variance technique adapted to account for both averaging over slow-time and depth. The blood amplitude and phase estimation technique (BAPES) is based on finding a set of matched filters (one for each velocity component of interest) and filtering the blood process over slow-time and averaging over depth to find the PSD. The methods are tested using various experiments and simulations. First, controlled flow-rig experiments with steady laminar flow are carried out. Simulations in Field II for pulsating flow resembling the femoral artery are also analyzed. The simulations are followed by in vivo measurement on the common carotid artery. In all simulations and experiments it was concluded that the adaptive methods display superior performance for short observation windows compared with the averaged periodogram. Computational costs and implementation details are also discussed.
authors.affiliation: GN ReSound A/S. Algorithm R&D, Ballerup, Denmark. fgran@gnresound.dk
authors.forename: Fredrik
authors.initials: F
authors.lastname: Gran
authors.forename: Andreas
authors.initials: A
authors.lastname: Jakobsson
authors.forename: Jørgen Arendt
authors.initials: JA
authors.lastname: Jensen
mesh_terms: D000818:Animals; D001158:Arteries / Q000000981:diagnostic imaging* / Q000502:physiology*; D001783:Blood Flow Velocity / Q000502:physiology*; D003198:Computer Simulation; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008955:Models, Cardiovascular; D012212:Rheology / Q000379:methods*; D018608:Ultrasonography, Doppler / Q000379:methods*