LymphedemaV1, Ncbi, Merge, bibRecord, 007309

Ultrasound 2D Strain Estimator Based on Image Registration for Ultrasound Elastography

Identifieur interne : 007309 ( Ncbi/Merge ); précédent : 007308; suivant : 007310

Ultrasound 2D Strain Estimator Based on Image Registration for Ultrasound Elastography

Auteurs : Xiaofeng Yang ; Mylin Torres ; Stephanie Kirkpatrick ; Walter J. Curran ; Tian Liu

Source :

Proceedings of SPIE--the International Society for Optical Engineering [ 0277-786X ] ; 2014.

RBID : PMC:4405672

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 in vivo 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 in vivo data from patients with arm lymphedema.

Url:

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4405672

DOI: 10.1117/12.2043865
PubMed: 25914492
PubMed Central: 4405672

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PMC:4405672

Le document en format XML

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 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>
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<front><div type="abstract" xml:lang="en">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 in vivo 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 in vivo data from patients with arm lymphedema.</div>
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Ultrasound 2D Strain Estimator Based on Image Registration for Ultrasound Elastography

Ultrasound 2D Strain Estimator Based on Image Registration for Ultrasound Elastography

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Abstract

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