Martínez Martínez, F.; Rupérez Moreno, MJ.; Martín Guerrero, JD.; Monserrat Aranda, C.; Lago, MA.; Pareja, E.; Brugger, S.... (2013). Estimation of the elastic parameters of human liver biomechanical models by means of medical images and evolutionary computation. Computer Methods and Programs in Biomedicine. 111(3):537-549. doi:10.1016/j.cmpb.2013.05.005
Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/43244
Title:
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Estimation of the elastic parameters of human liver biomechanical models by means of medical images and evolutionary computation
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Author:
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Martínez Martínez, Francisco
Rupérez Moreno, María José
Martín Guerrero, José David
Monserrat Aranda, Carlos
Lago, M. A.
Pareja, E.
Brugger, S.
López-Andújar, R.
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UPV Unit:
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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
Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
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Issued date:
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Abstract:
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This paper presents a method to computationally estimate the elastic parameters of two
biomechanical models proposed for the human liver. The method is aimed at avoiding the
invasive measurement of its mechanical response. ...[+]
This paper presents a method to computationally estimate the elastic parameters of two
biomechanical models proposed for the human liver. The method is aimed at avoiding the
invasive measurement of its mechanical response. The chosen models are a second order
Mooney–Rivlin model and an Ogden model. A novel error function, the geometric similarity
function (GSF), is formulated using similarity coefficients widely applied in the field of medical
imaging (Jaccard coefficient and Hausdorff coefficient). This function is used to compare
two 3D images. One of them corresponds to a reference deformation carried out over a finite
element (FE) mesh of a human liver from a computer tomography image, whilst the other
one corresponds to the FE simulation of that deformation in which variations in the values
of the model parameters are introduced. Several search strategies, based on GSF as cost
function, are developed to accurately find the elastics parameters of the models, namely:
two evolutionary algorithms (scatter search and genetic algorithm) and an iterative local
optimization. The results show that GSF is a very appropriate function to estimate the elastic
parameters of the biomechanical models since the mean of the relative mean absolute
errors committed by the three algorithms is lower than 4%.
© 2013 Elsevier Ireland Ltd. All rights reserved.
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Subjects:
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Biomechanical modeling
,
Liver
,
Jaccard
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Hausdorff
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Scatter search
,
Genetic algorithm
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Copyrigths:
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Cerrado |
Source:
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Computer Methods and Programs in Biomedicine. (issn:
0169-2607
)
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DOI:
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10.1016/j.cmpb.2013.05.005
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Publisher:
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Elsevier
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Publisher version:
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http://dx.doi.org/10.1016/j.cmpb.2013.05.005
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Project ID:
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CDTI [IDI-20101153]
MICINN [TIN2010-20999-C04-01]
Spanish Government under the FPI Grant [BES-2011-046495]
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Thanks:
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This project has been partially funded by CDTI (reference IDI-20101153) and by MICINN (reference TIN2010-20999-C04-01). The work of Francisco Martinez-Martinez has been supported by the Spanish Government under the FPI ...[+]
This project has been partially funded by CDTI (reference IDI-20101153) and by MICINN (reference TIN2010-20999-C04-01). The work of Francisco Martinez-Martinez has been supported by the Spanish Government under the FPI Grant BES-2011-046495. We would also like to express our gratitude to the Hospital Clinica Benidorm.
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Type:
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Artículo
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