Influence of ultrasound speckle tracking strategies for motion and strain estimation
- Autores
- Curiale, Ariel Hernán; Vegas Sánchez Ferrero, Gonzalo; Aja Fernández, Santiago
- Año de publicación
- 2016
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Speckle Tracking is one of the most prominent techniques used to estimate the regional movement of the heart based on ultrasound acquisitions. Many different approaches have been proposed, proving their suitability to obtain quantitative and qualitative information regarding myocardial deformation, motion and function assessment. New proposals to improve the basic algorithm usually focus on one of these three steps: (1) the similarity measure between images and the speckle model; (2) the transformation model, i.e. the type of motion considered between images; (3) the optimization strategies, such as the use of different optimization techniques in the transformation step or the inclusion of structural information. While many contributions have shown their good performance independently, it is not always clear how they perform when integrated in a whole pipeline. Every step will have a degree of influence over the following and hence over the final result. Thus, a Speckle Tracking pipeline must be analyzed as a whole when developing novel methods, since improvements in a particular step might be undermined by the choices taken in further steps. This work presents two main contributions: (1) We provide a complete analysis of the influence of the different steps in a Speckle Tracking pipeline over the motion and strain estimation accuracy. (2) The study proposes a methodology for the analysis of Speckle Tracking systems specifically designed to provide an easy and systematic way to include other strategies. We close the analysis with some conclusions and recommendations that can be used as an orientation of the degree of influence of the models for speckle, the transformation models, interpolation schemes and optimization strategies over the estimation of motion features. They can be further use to evaluate and design new strategy into a Speckle Tracking system.
Fil: Curiale, Ariel Hernán. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Cuyo. Facultad de Ciencias Exactas y Naturales; Argentina. Comisión Nacional de Energía Atómica. Centro Atómico Bariloche; Argentina. Fundación Escuela Medicina Nuclear; Argentina. Universidad de Valladolid; España
Fil: Vegas Sánchez Ferrero, Gonzalo. Harvard Medical School; Estados Unidos. Universidad Politécnica de Madrid; España
Fil: Aja Fernández, Santiago. Universidad de Valladolid; España - Materia
-
Demons Registration
Diffeomorphic Registration
Echocardiography
Generalized Gamma
Local Correlation
Maximum Likelihood
Mixture Model
Optical Flow
Speckle Model
Speckle Tracking
Strain Estimation
Ultrasound Images - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/59674
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Influence of ultrasound speckle tracking strategies for motion and strain estimationCuriale, Ariel HernánVegas Sánchez Ferrero, GonzaloAja Fernández, SantiagoDemons RegistrationDiffeomorphic RegistrationEchocardiographyGeneralized GammaLocal CorrelationMaximum LikelihoodMixture ModelOptical FlowSpeckle ModelSpeckle TrackingStrain EstimationUltrasound Imageshttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Speckle Tracking is one of the most prominent techniques used to estimate the regional movement of the heart based on ultrasound acquisitions. Many different approaches have been proposed, proving their suitability to obtain quantitative and qualitative information regarding myocardial deformation, motion and function assessment. New proposals to improve the basic algorithm usually focus on one of these three steps: (1) the similarity measure between images and the speckle model; (2) the transformation model, i.e. the type of motion considered between images; (3) the optimization strategies, such as the use of different optimization techniques in the transformation step or the inclusion of structural information. While many contributions have shown their good performance independently, it is not always clear how they perform when integrated in a whole pipeline. Every step will have a degree of influence over the following and hence over the final result. Thus, a Speckle Tracking pipeline must be analyzed as a whole when developing novel methods, since improvements in a particular step might be undermined by the choices taken in further steps. This work presents two main contributions: (1) We provide a complete analysis of the influence of the different steps in a Speckle Tracking pipeline over the motion and strain estimation accuracy. (2) The study proposes a methodology for the analysis of Speckle Tracking systems specifically designed to provide an easy and systematic way to include other strategies. We close the analysis with some conclusions and recommendations that can be used as an orientation of the degree of influence of the models for speckle, the transformation models, interpolation schemes and optimization strategies over the estimation of motion features. They can be further use to evaluate and design new strategy into a Speckle Tracking system.Fil: Curiale, Ariel Hernán. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Cuyo. Facultad de Ciencias Exactas y Naturales; Argentina. Comisión Nacional de Energía Atómica. Centro Atómico Bariloche; Argentina. Fundación Escuela Medicina Nuclear; Argentina. Universidad de Valladolid; EspañaFil: Vegas Sánchez Ferrero, Gonzalo. Harvard Medical School; Estados Unidos. Universidad Politécnica de Madrid; EspañaFil: Aja Fernández, Santiago. Universidad de Valladolid; EspañaElsevier Science2016-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/59674Curiale, Ariel Hernán; Vegas Sánchez Ferrero, Gonzalo; Aja Fernández, Santiago; Influence of ultrasound speckle tracking strategies for motion and strain estimation; Elsevier Science; Medical Image Analysis; 32; 8-2016; 184-2001361-8415CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.media.2016.04.002info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S1361841516300202info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:41:14Zoai:ri.conicet.gov.ar:11336/59674instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:41:15.25CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
Influence of ultrasound speckle tracking strategies for motion and strain estimation |
title |
Influence of ultrasound speckle tracking strategies for motion and strain estimation |
spellingShingle |
Influence of ultrasound speckle tracking strategies for motion and strain estimation Curiale, Ariel Hernán Demons Registration Diffeomorphic Registration Echocardiography Generalized Gamma Local Correlation Maximum Likelihood Mixture Model Optical Flow Speckle Model Speckle Tracking Strain Estimation Ultrasound Images |
title_short |
Influence of ultrasound speckle tracking strategies for motion and strain estimation |
title_full |
Influence of ultrasound speckle tracking strategies for motion and strain estimation |
title_fullStr |
Influence of ultrasound speckle tracking strategies for motion and strain estimation |
title_full_unstemmed |
Influence of ultrasound speckle tracking strategies for motion and strain estimation |
title_sort |
Influence of ultrasound speckle tracking strategies for motion and strain estimation |
dc.creator.none.fl_str_mv |
Curiale, Ariel Hernán Vegas Sánchez Ferrero, Gonzalo Aja Fernández, Santiago |
author |
Curiale, Ariel Hernán |
author_facet |
Curiale, Ariel Hernán Vegas Sánchez Ferrero, Gonzalo Aja Fernández, Santiago |
author_role |
author |
author2 |
Vegas Sánchez Ferrero, Gonzalo Aja Fernández, Santiago |
author2_role |
author author |
dc.subject.none.fl_str_mv |
Demons Registration Diffeomorphic Registration Echocardiography Generalized Gamma Local Correlation Maximum Likelihood Mixture Model Optical Flow Speckle Model Speckle Tracking Strain Estimation Ultrasound Images |
topic |
Demons Registration Diffeomorphic Registration Echocardiography Generalized Gamma Local Correlation Maximum Likelihood Mixture Model Optical Flow Speckle Model Speckle Tracking Strain Estimation Ultrasound Images |
purl_subject.fl_str_mv |
https://purl.org/becyt/ford/1.2 https://purl.org/becyt/ford/1 |
dc.description.none.fl_txt_mv |
Speckle Tracking is one of the most prominent techniques used to estimate the regional movement of the heart based on ultrasound acquisitions. Many different approaches have been proposed, proving their suitability to obtain quantitative and qualitative information regarding myocardial deformation, motion and function assessment. New proposals to improve the basic algorithm usually focus on one of these three steps: (1) the similarity measure between images and the speckle model; (2) the transformation model, i.e. the type of motion considered between images; (3) the optimization strategies, such as the use of different optimization techniques in the transformation step or the inclusion of structural information. While many contributions have shown their good performance independently, it is not always clear how they perform when integrated in a whole pipeline. Every step will have a degree of influence over the following and hence over the final result. Thus, a Speckle Tracking pipeline must be analyzed as a whole when developing novel methods, since improvements in a particular step might be undermined by the choices taken in further steps. This work presents two main contributions: (1) We provide a complete analysis of the influence of the different steps in a Speckle Tracking pipeline over the motion and strain estimation accuracy. (2) The study proposes a methodology for the analysis of Speckle Tracking systems specifically designed to provide an easy and systematic way to include other strategies. We close the analysis with some conclusions and recommendations that can be used as an orientation of the degree of influence of the models for speckle, the transformation models, interpolation schemes and optimization strategies over the estimation of motion features. They can be further use to evaluate and design new strategy into a Speckle Tracking system. Fil: Curiale, Ariel Hernán. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Cuyo. Facultad de Ciencias Exactas y Naturales; Argentina. Comisión Nacional de Energía Atómica. Centro Atómico Bariloche; Argentina. Fundación Escuela Medicina Nuclear; Argentina. Universidad de Valladolid; España Fil: Vegas Sánchez Ferrero, Gonzalo. Harvard Medical School; Estados Unidos. Universidad Politécnica de Madrid; España Fil: Aja Fernández, Santiago. Universidad de Valladolid; España |
description |
Speckle Tracking is one of the most prominent techniques used to estimate the regional movement of the heart based on ultrasound acquisitions. Many different approaches have been proposed, proving their suitability to obtain quantitative and qualitative information regarding myocardial deformation, motion and function assessment. New proposals to improve the basic algorithm usually focus on one of these three steps: (1) the similarity measure between images and the speckle model; (2) the transformation model, i.e. the type of motion considered between images; (3) the optimization strategies, such as the use of different optimization techniques in the transformation step or the inclusion of structural information. While many contributions have shown their good performance independently, it is not always clear how they perform when integrated in a whole pipeline. Every step will have a degree of influence over the following and hence over the final result. Thus, a Speckle Tracking pipeline must be analyzed as a whole when developing novel methods, since improvements in a particular step might be undermined by the choices taken in further steps. This work presents two main contributions: (1) We provide a complete analysis of the influence of the different steps in a Speckle Tracking pipeline over the motion and strain estimation accuracy. (2) The study proposes a methodology for the analysis of Speckle Tracking systems specifically designed to provide an easy and systematic way to include other strategies. We close the analysis with some conclusions and recommendations that can be used as an orientation of the degree of influence of the models for speckle, the transformation models, interpolation schemes and optimization strategies over the estimation of motion features. They can be further use to evaluate and design new strategy into a Speckle Tracking system. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-08 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
format |
article |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://hdl.handle.net/11336/59674 Curiale, Ariel Hernán; Vegas Sánchez Ferrero, Gonzalo; Aja Fernández, Santiago; Influence of ultrasound speckle tracking strategies for motion and strain estimation; Elsevier Science; Medical Image Analysis; 32; 8-2016; 184-200 1361-8415 CONICET Digital CONICET |
url |
http://hdl.handle.net/11336/59674 |
identifier_str_mv |
Curiale, Ariel Hernán; Vegas Sánchez Ferrero, Gonzalo; Aja Fernández, Santiago; Influence of ultrasound speckle tracking strategies for motion and strain estimation; Elsevier Science; Medical Image Analysis; 32; 8-2016; 184-200 1361-8415 CONICET Digital CONICET |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.media.2016.04.002 info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S1361841516300202 |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
dc.format.none.fl_str_mv |
application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
Elsevier Science |
publisher.none.fl_str_mv |
Elsevier Science |
dc.source.none.fl_str_mv |
reponame:CONICET Digital (CONICET) instname:Consejo Nacional de Investigaciones Científicas y Técnicas |
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CONICET Digital (CONICET) |
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CONICET Digital (CONICET) |
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Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.name.fl_str_mv |
CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.mail.fl_str_mv |
dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar |
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1844613303937007616 |
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13.070432 |