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Methodology based on genetic heuristics for in-vivo characterizing the patient-specific biomechanical behavior of the breast tissues

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Methodology based on genetic heuristics for in-vivo characterizing the patient-specific biomechanical behavior of the breast tissues

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dc.contributor.author Lago, M. A. es_ES
dc.contributor.author Rupérez Moreno, María José es_ES
dc.contributor.author Martínez Martínez, Francisco es_ES
dc.contributor.author Martinez-Sanchis, Sandra es_ES
dc.contributor.author Bakic, P.R. es_ES
dc.contributor.author Monserrat, C. es_ES
dc.date.accessioned 2020-09-19T03:34:00Z
dc.date.available 2020-09-19T03:34:00Z
dc.date.issued 2015-11-30 es_ES
dc.identifier.issn 0957-4174 es_ES
dc.identifier.uri http://hdl.handle.net/10251/150431
dc.description.abstract [EN] This paper presents a novel methodology to in-vivo estimate the elastic constants of a constitutive model proposed to characterize the mechanical behavior of the breast tissues. An iterative search algorithm based on genetic heuristics was constructed to in-vivo estimate these parameters using only medical images, thus avoiding invasive measurements of the mechanical response of the breast tissues. For the first time, a combination of overlap and distance coefficients were used for the evaluation of the similar- ity between a deformed MRI of the breast and a simulation of that deformation. The methodology was validated using breast software phantoms for virtual clinical trials, compressed to mimic MRI-guided biopsies. The biomechanical model chosen to characterize the breast tissues was an anisotropic neo-Hookean hyperelastic model. Results from this analysis showed that the algorithm is able to find the elastic constants of the constitutive equations of the proposed model with a mean relative error of about 10%. Furthermore, the overlap between the reference deformation and the simulated deformation was of around 95% showing the good performance of the proposed methodology. This methodology can be easily extended to characterize the real biomechanical behavior of the breast tissues, which means a great novelty in the field of the simulation of the breast behavior for applications such as surgical planing, surgical guidance or cancer diagnosis. This reveals the impact and relevance of the presented work. es_ES
dc.description.sponsorship This project has been funded by MECD (reference AP2009-2414) and US National Institutes of Health (R01 Grant #CA154444), and the US National Science Foundation (III Grant #0916690). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH, and NSF. The authors of this manuscript have no conflict of interest with the presented work es_ES
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation NIH/CA154444 es_ES
dc.relation NSF/0916690 es_ES
dc.relation info:eu-repo/grantAgreement/ME//AP2009-2414/ES/AP2009-2414/ es_ES
dc.relation.ispartof Expert Systems with Applications es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Genetic heuristics es_ES
dc.subject In-vivo tissue characterization es_ES
dc.subject Breast biomechanical modeling es_ES
dc.subject Parameter estimation es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.subject.classification INGENIERIA MECANICA es_ES
dc.title Methodology based on genetic heuristics for in-vivo characterizing the patient-specific biomechanical behavior of the breast tissues es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.eswa.2015.05.058 es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Mecánica y de Materiales - Departament d'Enginyeria Mecànica i de Materials es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto Interuniversitario de Investigación en Bioingeniería y Tecnología Orientada al Ser Humano - Institut Interuniversitari d'Investigació en Bioenginyeria i Tecnologia Orientada a l'Ésser Humà es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació es_ES
dc.description.bibliographicCitation Lago, MA.; Rupérez Moreno, MJ.; Martínez Martínez, F.; Martinez-Sanchis, S.; Bakic, P.; Monserrat, C. (2015). Methodology based on genetic heuristics for in-vivo characterizing the patient-specific biomechanical behavior of the breast tissues. Expert Systems with Applications. 42(21):7942-7950. https://doi.org/10.1016/j.eswa.2015.05.058 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1016/j.eswa.2015.05.058 es_ES
dc.description.upvformatpinicio 7942 es_ES
dc.description.upvformatpfin 7950 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 42 es_ES
dc.description.issue 21 es_ES
dc.identifier.pmid 27103760 es_ES
dc.identifier.pmcid PMC4834716 es_ES
dc.relation.pasarela S\292012 es_ES
dc.contributor.funder Ministerio de Educación es_ES
dc.contributor.funder National Science Foundation, EEUU es_ES
dc.contributor.funder National Institutes of Health, EEUU es_ES


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