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dc.contributor.author
Curiale, Ariel Hernán
dc.contributor.author
Vegas Sánchez Ferrero, Gonzalo
dc.contributor.author
Aja Fernández, Santiago
dc.date.available
2018-09-14T14:46:11Z
dc.date.issued
2016-08
dc.identifier.citation
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
dc.identifier.issn
1361-8415
dc.identifier.uri
http://hdl.handle.net/11336/59674
dc.description.abstract
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.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Elsevier Science
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
Demons Registration
dc.subject
Diffeomorphic Registration
dc.subject
Echocardiography
dc.subject
Generalized Gamma
dc.subject
Local Correlation
dc.subject
Maximum Likelihood
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Mixture Model
dc.subject
Optical Flow
dc.subject
Speckle Model
dc.subject
Speckle Tracking
dc.subject
Strain Estimation
dc.subject
Ultrasound Images
dc.subject.classification
Ciencias de la Computación
dc.subject.classification
Ciencias de la Computación e Información
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS
dc.title
Influence of ultrasound speckle tracking strategies for motion and strain estimation
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2018-09-14T14:17:09Z
dc.journal.volume
32
dc.journal.pagination
184-200
dc.journal.pais
Países Bajos
dc.journal.ciudad
Amsterdam
dc.description.fil
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
dc.description.fil
Fil: Vegas Sánchez Ferrero, Gonzalo. Harvard Medical School; Estados Unidos. Universidad Politécnica de Madrid; España
dc.description.fil
Fil: Aja Fernández, Santiago. Universidad de Valladolid; España
dc.journal.title
Medical Image Analysis
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/https://dx.doi.org/10.1016/j.media.2016.04.002
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S1361841516300202
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