Comparison of Filtering Techniques in Ultrasound Color Flow Imaging


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Abstract

The article considers filtering techniques used to suppress clutter signals from moving tissues and to improve reliability of blood flow estimation. It compares polynomial and adaptive bases such as the result of empirical mode decomposition and singular vectors obtained through Karhunen−Loève transform. Filtering techniques are examined using a computer-simulated model, Doppler flow phantom and in vivo data. Filters are compared in terms of computational complexity, ability to retrieve flow profile without errors and through ROC curve analysis. Polynomial regression filters with tissue phase shift compensation were found to be the best fit for clutter suppression in terms of computational demands and accuracy of velocity estimation.

About the authors

D. V. Leonov

Research and Practical Clinical Center of Diagnostics and Telemedicine Technologies, Department of Healthcare of Moscow

Author for correspondence.
Email: d.leonov@npcmr.ru
Russian Federation, Moscow

N. S. Kulberg

Research and Practical Clinical Center of Diagnostics and Telemedicine Technologies, Department of Healthcare of Moscow

Email: d.leonov@npcmr.ru
Russian Federation, Moscow

V. A. Fin

National Research University “Moscow Power Engineering Institute”

Email: d.leonov@npcmr.ru
Russian Federation, Moscow

V. A. Podmoskovnaya

National Research University “Moscow Power Engineering Institute”

Email: d.leonov@npcmr.ru
Russian Federation, Moscow

L. S. Ivanova

National Research University “Moscow Power Engineering Institute”

Email: d.leonov@npcmr.ru
Russian Federation, Moscow

A. S. Shipaeva

National Research University “Moscow Power Engineering Institute”

Email: d.leonov@npcmr.ru
Russian Federation, Moscow

A. V. Vladzimirskiy

Research and Practical Clinical Center of Diagnostics and Telemedicine Technologies, Department of Healthcare of Moscow

Email: d.leonov@npcmr.ru
Russian Federation, Moscow

S. P. Morozov

Research and Practical Clinical Center of Diagnostics and Telemedicine Technologies, Department of Healthcare of Moscow

Email: d.leonov@npcmr.ru
Russian Federation, Moscow

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