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Basic study on estimation method of wall shear stress in common carotid artery using blood flow imaging

Nagaoka, Ryo (author)
University of Toyama
Ishikawa, Kazuma (author)
University of Toyama
Mozumi, Michiya (author)
University of Toyama
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Cinthio, Magnus (author)
Lund University,Lunds universitet,Avdelningen för Biomedicinsk teknik,Institutionen för biomedicinsk teknik,Institutioner vid LTH,Lunds Tekniska Högskola,Department of Biomedical Engineering,Departments at LTH,Faculty of Engineering, LTH
Hasegawa, Hideyuki (author)
University of Toyama
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 (creator_code:org_t)
2020-04-29
2020
English.
In: Japanese Journal of Applied Physics. - : IOP Publishing. - 0021-4922 .- 1347-4065. ; 59
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • In this paper, we propose a method for adaptive selection of the kernel size used in estimation of the wall shear stress (WSS) based on flow velocity profiles obtained by the blood flow imaging method based on enhancement of RF echo signals from blood cells using a singular value decomposition based clutter filter. Two simulation phantom experiments with the Field II program were performed to validate the proposed method. In the simulation experiments, the average bias error (BE) between the WSSs estimated by the conventional method and theoretical one was 16.5%. The proposed method could reduce the average BE to 12.3%. Also, the proposed method was applied to RF echo signals from a common carotid artery (CCA) of a healthy male subject. The WSSs in the CCA were estimated during one cardiac cycle and in a range similar to that in previous reports.

Subject headings

MEDICIN OCH HÄLSOVETENSKAP  -- Medicinsk bioteknologi -- Biomedicinsk laboratorievetenskap/teknologi (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Medical Biotechnology -- Biomedical Laboratory Science/Technology (hsv//eng)

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Nagaoka, Ryo
Ishikawa, Kazuma
Mozumi, Michiya
Cinthio, Magnus
Hasegawa, Hideyu ...
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MEDICAL AND HEALTH SCIENCES
MEDICAL AND HEAL ...
and Medical Biotechn ...
and Biomedical Labor ...
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Lund University

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