Paper
11 April 2002 Spatio-temporal analysis of color Doppler information using independent component analysis
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Abstract
Observing the correlation between the information in neighboring resolution cells, we propose a methodology to allow better analysis of Doppler ultrasound signals. A blind source separation problem is formulated to discern the different signal components for correct interpretation of the data using independent component analysis (ICA). The Doppler signal is modeled as the summation of the true velocity signal, baseline fluctuation, and random noise. The baseline fluctuation component can be considered as a deterministic yet unknown signal. A simple adaptive denoising technique is applied to reduce the effective dimension of the noise subspace. Then, given a region of interest, the temporal signals corresponding to all pixels within this region undergo the ICA iteration to compute a set of independent signals that most represent the actual components present within the data. Subsequently, a comparison of the temporal variations of these signals allows the user identify the components of the signals that correspond to baseline variation or random noise manually or using semi-automated techniques. The new technique shows large potential to alleviate some of the limitations in this demanding imaging mode as well as to make the interpretation of the results more robust.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yasser M. Kadah "Spatio-temporal analysis of color Doppler information using independent component analysis", Proc. SPIE 4687, Medical Imaging 2002: Ultrasonic Imaging and Signal Processing, (11 April 2002); https://doi.org/10.1117/12.462158
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Cited by 5 scholarly publications.
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KEYWORDS
Independent component analysis

Principal component analysis

Signal processing

Doppler effect

Interference (communication)

Denoising

Data modeling

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