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3D Cohesive Finite Element Minimum Invasive Surgery Simulation Based on Kelvin-Voigt Model

Yonghang Jiang et al · KeAi Communications Co., Ltd · 2022

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Abstract Minimally invasive surgery is an important technique used for cytopathological examination. Recently, multiple studies have been conducted on a three-dimensional (3D) puncture simulation model as it can reveal the internal deformation state of the tissue at the micro level. In this study, a viscoelastic constitutive equation suitable for muscle tissue was derived. Additionally, a method was developed to define the fracture characteristics of muscle tissue material during the simulation process. The fracture of the muscle tissue in contact with the puncture needle was simulated using the cohesive zone model and a 3D puncture finite element model was established to analyze the deformation of the muscle tissue. The stress nephogram and reaction force under different parameters were compared and analyzed to study the deformation of the biological soft tissue and guide the actual operation process and reduce pain.

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APA 7

al, Y. J. E. (2022). 3D Cohesive Finite Element Minimum Invasive Surgery Simulation Based on Kelvin-Voigt Model. https://doi.org/10.1186/s10033-022-00743-y

MLA

al, Yonghang Jiang et. "3D Cohesive Finite Element Minimum Invasive Surgery Simulation Based on Kelvin-Voigt Model." 2022. https://doi.org/10.1186/s10033-022-00743-y.

Chicago

al, Yonghang Jiang et. 2022. "3D Cohesive Finite Element Minimum Invasive Surgery Simulation Based on Kelvin-Voigt Model.". https://doi.org/10.1186/s10033-022-00743-y.

Harvard

al, Y. J. E. 2022, 3D Cohesive Finite Element Minimum Invasive Surgery Simulation Based on Kelvin-Voigt Model, KeAi Communications Co, Ltd, available at: https://doi.org/10.1186/s10033-022-00743-y [Accessed 7 Aug. 2026].

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Title
3D Cohesive Finite Element Minimum Invasive Surgery Simulation Based on Kelvin-Voigt Model
Author / contributors
Yonghang Jiang et al
Publisher
KeAi Communications Co., Ltd
Publication year
2022
ISSN
1000-9345
ISSN
1000-9345
Language
English

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