| Comparison of physiological motion filters for in vivo cardiac ARFI. | |
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MedLine Citation:
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PMID: 21710825 Owner: NLM Status: In-Process |
Abstract/OtherAbstract:
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Acoustic radiation force impulse (ARFI) imaging is being utilized to investigate mechanical properties ofcardiac tissue. The underlying physiological motion, however, presents a major challenge. This paper aims to investigate the effectiveness of various physiological motion filters using in vivo canine data with a simulated ARFI push pulse. Ideally, the motion filter will exactly model the physiological motion and, when subtracted from the total displacement, leave only the simulated ARFI displacement profile. We investigated three temporal quadratic motion filters: (1)interpolation, (2) extrapolation and (3) a weighted technique. Additionally, the various motion filters were compared when using 1-D versus 2-D autocorrelation methods to estimate motion. It was found that 2D-autocorrelation always produced better physiological motion estimates regardless of the type of filter used. The extrapolation filter gives the most accurate estimate of the physiological motion at times immediately after the ARFI push (0.1 ms) while a close-time interpolation filter using displacement estimates at times before full tissue recovery gives the most accurate estimates at later times after the ARFI push (0.7 ms). While improvements to the motion filter during atrial systole and the onset of ventricular systole are needed, the weighted, close-time interpolation and extrapolation motion filters all offer promising results for estimating cardiac physiological motion more accurately, while allowing faster ARFI frame rates than previous motion filters. This study demonstrates the ability to eliminate physiological motion in a clinically-feasible manner, opening the door for more extensive clinical experimentation. |
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Authors:
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Doug M Giannantonio; Douglas M Dumont; Gregg E Trahey; Brett C Byram |
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Publication Detail:
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Type: Journal Article; Research Support, N.I.H., Extramural |
Journal Detail:
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Title: Ultrasonic imaging Volume: 33 ISSN: 0161-7346 ISO Abbreviation: Ultrason Imaging Publication Date: 2011 Apr |
Date Detail:
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Created Date: 2011-06-29 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 7909167 Medline TA: Ultrason Imaging Country: United States |
Other Details:
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Languages: eng Pagination: 89-108 Citation Subset: IM |
Affiliation:
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Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA. doug@giannantonio.com |
Export Citation:
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Descriptor/Qualifier:
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| Grant Support | |
ID/Acronym/Agency:
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T32EB001040/EB/NIBIB NIH HHS |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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