Comparison of Filtering Techniques in Ultrasound Color Flow Imaging
- Authors: Leonov D.V.1, Kulberg N.S.1, Fin V.A.2, Podmoskovnaya V.A.2, Ivanova L.S.2, Shipaeva A.S.2, Vladzimirskiy A.V.1, Morozov S.P.1
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Affiliations:
- Research and Practical Clinical Center of Diagnostics and Telemedicine Technologies, Department of Healthcare of Moscow
- National Research University “Moscow Power Engineering Institute”
- Issue: Vol 53, No 2 (2019)
- Pages: 97-101
- Section: Article
- URL: https://journals.rcsi.science/0006-3398/article/view/236041
- DOI: https://doi.org/10.1007/s10527-019-09885-1
- ID: 236041
Cite item
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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