Comparison of singular value decomposition filter frameworks for pre- and post-beamformed data of blood flow echo signals

Abstract Singular value decomposition (SVD)-based clutter filters effectively separate tissue, blood flow, and noise components. This study compares post-beamformed (conventional) and pre-beamformed (proposed) data with SVD-based filters to enhance the blood flow echo. Using simulation, experimental, and in vivo data, the image contrast was evaluated in the blood flow against different locations in near- and far-tissues, and blood flow itself. The suppression of the tissue component improved more in the proposed method while the conventional method achieved comparable or higher contrast in blood flow itself. This improvement was attributed to better suppression of tissue signals in the pre-beamformed processing. Ultrasound imaging provides a non-invasive, real-time diagnostic tool, making it highly suitable for detecting cardiovascular diseases. The diagnostic procedure involves obtaining ultrasound imaging from blood vessels in B-mode image and evaluating blood flow echoes in Doppler ultrasound. The visualization of blood flow echo can assess blood properties such as flow velocity and smoke-like echo.