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Improved tracking performance of lagrangian block-matching methodologies using block expansion in the time domain: In silico, phantom and invivo evaluations
Lund Univ, Dept Biomed Engn, S-22100 Lund, Sweden..
Halmstad University, School of Business, Engineering and Science, The Rydberg Laboratory for Applied Sciences (RLAS).
Lund Univ, Dept Clin Sci, Clin Physiol & Nucl Med Unit, Malmo, Sweden..
Lund Univ, Dept Biomed Engn, S-22100 Lund, Sweden..
2014 (English)In: Ultrasound in Medicine and Biology, ISSN 0301-5629, E-ISSN 1879-291X, Vol. 40, no 10, p. 2508-2520Article in journal (Refereed) Published
Abstract [en]

The aim of this study was to evaluate tracking performance when an extra reference block is added to a basic block-matching method, where the two reference blocks originate from two consecutive ultrasound frames. The use of an extra reference block was evaluated for two putative benefits: (i) an increase in tracking performance while maintaining the size of the reference blocks, evaluated using in silico and phantom cine loops; (ii) a reduction in the size of the reference blocks while maintaining the tracking performance, evaluated using in vivo cine loops of the common carotid artery where the longitudinal movement of the wall was estimated. The results indicated that tracking accuracy improved (mean - 48%, p<0.005 [in silico]; mean - 43%, p<0.01 [phantom]), and there was a reduction in size of the reference blocks while maintaining tracking performance (mean - 19%, p<0.01 [in vivo]). This novel method will facilitate further exploration of the longitudinal movement of the arterial wall. (C) 2014 World Federation for Ultrasound in Medicine & Biology.

Place, publisher, year, edition, pages
Elsevier, 2014. Vol. 40, no 10, p. 2508-2520
Keyword [en]
Ultrasound, Motion estimation, Longitudinal movement, Speckle tracking, Arterial wall movement
National Category
Medical Image Processing Radiology, Nuclear Medicine and Medical Imaging Computer Vision and Robotics (Autonomous Systems) Signal Processing
Identifiers
URN: urn:nbn:se:hh:diva-35444DOI: 10.1016/j.ultrasmedbio.2014.05.010ISI: 000343144400020PubMedID: 25130445Scopus ID: 2-s2.0-84926250866OAI: oai:DiVA.org:hh-35444DiVA: diva2:1159482
Available from: 2017-11-22 Created: 2017-11-22 Last updated: 2018-01-13Bibliographically approved

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Brorsson, Sofia

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Medical Image ProcessingRadiology, Nuclear Medicine and Medical ImagingComputer Vision and Robotics (Autonomous Systems)Signal Processing

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