Ultrasound 2D Strain Estimator Based on Image Registration for Ultrasound Elastography.
Identifieur interne : 000F25 ( PubMed/Curation ); précédent : 000F24; suivant : 000F26Ultrasound 2D Strain Estimator Based on Image Registration for Ultrasound Elastography.
Auteurs : Xiaofeng Yang [États-Unis] ; Mylin Torres [États-Unis] ; Stephanie Kirkpatrick [États-Unis] ; Walter J. Curran [États-Unis] ; Tian Liu [États-Unis]Source :
- 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 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.
DOI: 10.1117/12.2043865
PubMed: 25914492
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Curran</name><affiliation wicri:level="2"><nlm:affiliation>Department of Radiation Oncology, Winship Cancer Institute, Emory University, Atlanta, GA 30322.</nlm:affiliation><country xml:lang="fr">États-Unis</country><placeName><region type="state">Géorgie (États-Unis)</region></placeName><wicri:cityArea>Department of Radiation Oncology, Winship Cancer Institute, Emory University, Atlanta</wicri:cityArea></affiliation></author><author><name sortKey="Liu, Tian" sort="Liu, Tian" uniqKey="Liu T" first="Tian" last="Liu">Tian Liu</name><affiliation wicri:level="2"><nlm:affiliation>Department of Radiation Oncology, Winship Cancer Institute, Emory University, Atlanta, GA 30322.</nlm:affiliation><country xml:lang="fr">États-Unis</country><placeName><region type="state">Géorgie (États-Unis)</region></placeName><wicri:cityArea>Department of Radiation Oncology, Winship Cancer Institute, Emory University, Atlanta</wicri:cityArea></affiliation></author></analytic><series><title level="j">Proceedings of SPIE--the International Society for Optical Engineering</title><idno type="ISSN">0277-786X</idno><imprint><date when="2014" type="published">2014</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><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></front></TEI><pubmed><MedlineCitation Status="Publisher" Owner="NLM"><PMID Version="1">25914492</PMID><DateCreated><Year>2015</Year><Month>04</Month><Day>27</Day></DateCreated><DateRevised><Year>2017</Year><Month>02</Month><Day>20</Day></DateRevised><Article PubModel="Print"><Journal><ISSN IssnType="Print">0277-786X</ISSN><JournalIssue CitedMedium="Print"><Volume>9040</Volume><PubDate><Year>2014</Year><Month>Mar</Month><Day>20</Day></PubDate></JournalIssue><Title>Proceedings of SPIE--the International Society for Optical Engineering</Title><ISOAbbreviation>Proc SPIE Int Soc Opt Eng</ISOAbbreviation></Journal><ArticleTitle>Ultrasound 2D Strain Estimator Based on Image Registration for Ultrasound Elastography.</ArticleTitle><ELocationID EIdType="pii" ValidYN="Y">904018</ELocationID><Abstract><AbstractText>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.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Yang</LastName><ForeName>Xiaofeng</ForeName><Initials>X</Initials><AffiliationInfo><Affiliation>Department of Radiation Oncology, Winship Cancer Institute, Emory University, Atlanta, GA 30322.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Torres</LastName><ForeName>Mylin</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Department of Radiation Oncology, Winship Cancer Institute, Emory University, Atlanta, GA 30322.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Kirkpatrick</LastName><ForeName>Stephanie</ForeName><Initials>S</Initials><AffiliationInfo><Affiliation>Department of Radiation Oncology, Winship Cancer Institute, Emory University, Atlanta, GA 30322.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Curran</LastName><ForeName>Walter J</ForeName><Initials>WJ</Initials><AffiliationInfo><Affiliation>Department of Radiation Oncology, Winship Cancer Institute, Emory University, Atlanta, GA 30322.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Liu</LastName><ForeName>Tian</ForeName><Initials>T</Initials><AffiliationInfo><Affiliation>Department of Radiation Oncology, Winship Cancer Institute, Emory University, Atlanta, GA 30322.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><GrantList CompleteYN="Y"><Grant><GrantID>K01 CA114313</GrantID><Acronym>CA</Acronym><Agency>NCI NIH HHS</Agency><Country>United States</Country></Grant></GrantList><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>Proc SPIE Int Soc Opt Eng</MedlineTA><NlmUniqueID>101524122</NlmUniqueID><ISSNLinking>0277-786X</ISSNLinking></MedlineJournalInfo><CommentsCorrectionsList><CommentsCorrections RefType="Cites"><RefSource>Phys Med Biol. 2007 Jul 7;52(13):3773-90</RefSource><PMID Version="1">17664576</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>Proc Inst Mech Eng H. 1999;213(3):203-33</RefSource><PMID Version="1">10420776</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>IEEE Trans Med Imaging. 1999 Jul;18(7):593-603</RefSource><PMID Version="1">10504093</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>IEEE Trans Med Imaging. 1999 Aug;18(8):712-21</RefSource><PMID Version="1">10534053</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>Annu Rev Biomed Eng. 2003;5:57-78</RefSource><PMID Version="1">12704084</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>IEEE Trans Ultrason Ferroelectr Freq 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