Real‐time simulation of biological soft tissues: a PGD approach

Niroomandi, Siamak; González, David; Alfaro, Icíar; Bordeu, Felipe; Leygue, Adrien; Cueto, Elías; Chinesta, Francisco

doi:10.1002/cnm.2544

Cited by 81 publications

(80 citation statements)

References 38 publications

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“…In view of that, we have assumed a simplified Kirchhoff-Saint Venant model, with Young's modulus of 1.60 kPa, and a Poisson coefficient of 0.48, thus nearly incompressible [25]. This constitutes just a simplification that should be validated with the help of experienced surgeons, but remains valid as long as more complex models can be developed within the PGD techniques exposed before without any difficulty [26].…”

Section: Livermentioning

confidence: 99%

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Towards a pancreatic surgery simulator based on model order reduction

Mena

Bel

Alfaro

et al. 2015

Adv. Model. and Simul. in Eng. Sci.

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In this work a pancreatic surgery simulator is developed that provides the user with haptic feedback. The simulator is based on the use of model order reduction techniques, particularly Proper Generalized Decomposition methods. The just developed simulator presents some notable advancements with respect to existing works in the literature, such as the consideration of non-linear hyperelasticity for the constitutive modeling of soft tissues, an accurate description of contact between organs and momentum and energy conserving time integration schemes. Pancreas, liver, gall bladder, and duodenum are modeled in the simulator, thus providing with a very realistic and immersive perception to the user.

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Section: Livermentioning

confidence: 99%

“…The applied load was divided into three load steps, following the technique presented in [26], where an explicit algorithm was developed. This is why the error seems to reach two intermediate plateaus.…”

Section: Performancementioning

confidence: 99%

Towards a pancreatic surgery simulator based on model order reduction

Mena

Bel

Alfaro

et al. 2015

Adv. Model. and Simul. in Eng. Sci.

View full text Add to dashboard Cite

show abstract

“…At each direction of the fixed point algorithm, we face again a non-linear problem, due to the non-linear constitutive equations of the liver tissue. In [40,41], two distinct approaches have been pursued, namely an explicit one and a combination of PGD and asymptotic expansions on the variables of interest. The interested reader is committed to read these references for more details on the implementation.…”

Section: Simulation Of Liver Palpationmentioning

confidence: 99%

Real-time in silico experiments on gene regulatory networks and surgery simulation on handheld devices

et al. 2014

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Simulation of all phenomena taking place in a surgical procedure is a formidable task that involves, when possible, the use of supercomputing facilities over long time periods. However, decision taking in the operating room needs for fast methods that provide an accurate response in real time. To this end, Model Order Reduction (MOR) techniques have emerged recently in the field of Computational Surgery to help alleviate this burden. In this paper, we review the basics of classical MOR and explain how a technique recently developed by the authors and coined as Proper Generalized Decomposition could make real-time feedback available with the use of simple devices like smartphones or tablets. Examples are given on the performance of the technique for problems at different scales of the surgical procedure, form gene regulatory networks to macroscopic soft tissue deformation and cutting.

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“…Indeed, for a vast range of problems, only moderate number of enrichments and few iterations within each enrichment are required. Naturally, less solution data needs to be stored which is crucial in real-time simulations [7]. The PGD method also relies on the separability of the problem.…”

Section: Introductionmentioning

confidence: 99%

Application of PGD on Parametric Modeling of a Piezoelectric Energy Harvester

et al. 2016

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In this paper, a priori model reduction methods via low-rank tensor approximation are introduced for the parametric study of a piezoelectric energy harvester (EH). The EH, comprised of a cantilevered piezoelectric bimorph connected with electrical loads, is modeled using three dimensional finite elements (FEs). Solving the model for various excitation frequencies and electrical load using the conventional approach results in a large size problem that is costly in terms of CPU time. We propose an approach based on the proper generalized decomposition (PGD) that can effectively reduce the problem size with a good accuracy of the solutions. With the proposed approach, field variables of the coupled problem are decomposed into space, frequency and electrical load associated components. To introduce PGD into the FE model, a method to model the electrodes and electrical charges in the EH is presented. Appropriate choice for stopping criterions in the method, as well as accelerating the convergence through updating after each enrichment are investigated. The proposed method is validated through a representative numerical example.

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Real‐time simulation of biological soft tissues: a PGD approach

Cited by 81 publications

References 38 publications

Towards a pancreatic surgery simulator based on model order reduction

Towards a pancreatic surgery simulator based on model order reduction

Real-time in silico experiments on gene regulatory networks and surgery simulation on handheld devices

Application of PGD on Parametric Modeling of a Piezoelectric Energy Harvester

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