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dc.contributor.authorAvilés Rivero, Angélica Ivone
dc.contributor.authorWidlak, Thomas
dc.contributor.authorCasals Gelpí, Alicia
dc.contributor.authorNillesen, Maartje M.
dc.contributor.authorAmmari, Habib
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial
dc.date.accessioned2017-09-05T08:58:08Z
dc.date.available2017-09-05T08:58:08Z
dc.date.issued2017-06-21
dc.identifier.citationAvilés, A., Widlak, T., Casals, A., Nillesen, M., Ammari, H. Robust cardiac motion estimation using ultrafast ultrasound data: a low-rank topology-preserving approach. "Physics in medicine and biology", 21 Juny 2017, vol. 62, núm. 12, p. 4831-4851.
dc.identifier.issn0031-9155
dc.identifier.urihttp://hdl.handle.net/2117/107383
dc.description.abstractCardiac motion estimation is an important diagnostic tool for detecting heart diseases and it has been explored with modalities such as MRI and conventional ultrasound (US) sequences. US cardiac motion estimation still presents challenges because of complex motion patterns and the presence of noise. In this work, we propose a novel approach to estimate cardiac motion using ultrafast ultrasound data. Our solution is based on a variational formulation characterized by the L 2-regularized class. Displacement is represented by a lattice of b-splines and we ensure robustness, in the sense of eliminating outliers, by applying a maximum likelihood type estimator. While this is an important part of our solution, the main object of this work is to combine low-rank data representation with topology preservation. Low-rank data representation (achieved by finding the k-dominant singular values of a Casorati matrix arranged from the data sequence) speeds up the global solution and achieves noise reduction. On the other hand, topology preservation (achieved by monitoring the Jacobian determinant) allows one to radically rule out distortions while carefully controlling the size of allowed expansions and contractions. Our variational approach is carried out on a realistic dataset as well as on a simulated one. We demonstrate how our proposed variational solution deals with complex deformations through careful numerical experiments. The low-rank constraint speeds up the convergence of the optimization problem while topology preservation ensures a more accurate displacement. Beyond cardiac motion estimation, our approach is promising for the analysis of other organs that exhibit motion.
dc.format.extent21 p.
dc.language.isoeng
dc.subjectÀrees temàtiques de la UPC::Enginyeria biomèdica
dc.subject.lcshHeart -- Imaging
dc.subject.lcshDiagnosis, Ultrasonic
dc.subject.otherUltrafast ultrasound
dc.subject.otherLow-rank representation
dc.subject.otherTopology preservation
dc.subject.otherCardiac analysis
dc.subject.otherMotion estimation
dc.titleRobust cardiac motion estimation using ultrafast ultrasound data: a low-rank topology-preserving approach
dc.typeArticle
dc.subject.lemacCor -- Imatges
dc.subject.lemacDiagnòstic ultrasònic
dc.contributor.groupUniversitat Politècnica de Catalunya. GRINS - Grup de Recerca en Robòtica Intel·ligent i Sistemes
dc.identifier.doi10.1088/1361-6560/aa6914
dc.relation.publisherversionhttp://iopscience.iop.org/article/10.1088/1361-6560/aa6914/meta;jsessionid=CCC3EC9D9B98EDDE06297E5F08F19D51.c3.iopscience.cld.iop.org
dc.rights.accessOpen Access
local.identifier.drac21100213
dc.description.versionPostprint (author's final draft)
local.citation.authorAvilés, A.; Widlak, T.; Casals, A.; Nillesen, M.; Ammari, H.
local.citation.publicationNamePhysics in medicine and biology
local.citation.volume62
local.citation.number12
local.citation.startingPage4831
local.citation.endingPage4851


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