Ultrasound 2D Strain Estimator Based on Image Registration for Ultrasound Elastography
Identifieur interne : 007309 ( Ncbi/Checkpoint ); précédent : 007308; suivant : 007310Ultrasound 2D Strain Estimator Based on Image Registration for Ultrasound Elastography
Auteurs : Xiaofeng Yang ; Mylin Torres ; Stephanie Kirkpatrick ; Walter J. Curran ; Tian LiuSource :
- Proceedings of SPIE--the International Society for Optical Engineering [ 0277-786X ] ; 2014.
Abstract
In this paper, we present a new approach to calculate 2D strain through the registration of the pre- and post-compression (deformation) B-mode image sequences based on an intensity-based non-rigid registration algorithm (INRA). Compared with the most commonly used cross-correlation (CC) method, our approach is not constrained to any particular set of directions, and can overcome displacement estimation errors introduced by incoherent motion and variations in the signal under high compression. This INRA method was tested using phantom and
Url:
DOI: 10.1117/12.2043865
PubMed: 25914492
PubMed Central: 4405672
Affiliations:
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<author><name sortKey="Yang, Xiaofeng" sort="Yang, Xiaofeng" uniqKey="Yang X" first="Xiaofeng" last="Yang">Xiaofeng Yang</name>
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<author><name sortKey="Torres, Mylin" sort="Torres, Mylin" uniqKey="Torres M" first="Mylin" last="Torres">Mylin Torres</name>
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<author><name sortKey="Kirkpatrick, Stephanie" sort="Kirkpatrick, Stephanie" uniqKey="Kirkpatrick S" first="Stephanie" last="Kirkpatrick">Stephanie Kirkpatrick</name>
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<author><name sortKey="Curran, Walter J" sort="Curran, Walter J" uniqKey="Curran W" first="Walter J." last="Curran">Walter J. Curran</name>
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<author><name sortKey="Liu, Tian" sort="Liu, Tian" uniqKey="Liu T" first="Tian" last="Liu">Tian Liu</name>
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<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Ultrasound 2D Strain Estimator Based on Image Registration for Ultrasound Elastography</title>
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<author><name sortKey="Torres, Mylin" sort="Torres, Mylin" uniqKey="Torres M" first="Mylin" last="Torres">Mylin Torres</name>
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<author><name sortKey="Kirkpatrick, Stephanie" sort="Kirkpatrick, Stephanie" uniqKey="Kirkpatrick S" first="Stephanie" last="Kirkpatrick">Stephanie Kirkpatrick</name>
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<author><name sortKey="Curran, Walter J" sort="Curran, Walter J" uniqKey="Curran W" first="Walter J." last="Curran">Walter J. Curran</name>
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<author><name sortKey="Liu, Tian" sort="Liu, Tian" uniqKey="Liu T" first="Tian" last="Liu">Tian Liu</name>
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<front><div type="abstract" xml:lang="en"><p id="P1">In this paper, we present a new approach to calculate 2D strain through the registration of the pre- and post-compression (deformation) B-mode image sequences based on an intensity-based non-rigid registration algorithm (INRA). Compared with the most commonly used cross-correlation (CC) method, our approach is not constrained to any particular set of directions, and can overcome displacement estimation errors introduced by incoherent motion and variations in the signal under high compression. This INRA method was tested using phantom and <italic>in vivo</italic>
data. The robustness of our approach was demonstrated in the axial direction as well as the lateral direction where the standard CC method frequently fails. In addition, our approach copes well under large compression (over 6%). In the phantom study, we computed the strain image under various compressions and calculated the signal-to-noise (SNR) and contrast-to-noise (CNS) ratios. The SNR and CNS values of the INRA method were much higher than those calculated from the CC-based method. Furthermore, the clinical feasibility of our approach was demonstrated with the <italic>in vivo</italic>
data from patients with arm lymphedema.</p>
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<name sortKey="Liu, Tian" sort="Liu, Tian" uniqKey="Liu T" first="Tian" last="Liu">Tian Liu</name>
<name sortKey="Torres, Mylin" sort="Torres, Mylin" uniqKey="Torres M" first="Mylin" last="Torres">Mylin Torres</name>
<name sortKey="Yang, Xiaofeng" sort="Yang, Xiaofeng" uniqKey="Yang X" first="Xiaofeng" last="Yang">Xiaofeng Yang</name>
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