Soft tissue deformation modelling through neural dynamics-based reaction-diffusion mechanics.
Soft tissue deformation modelling forms the basis of development of surgical simulation, surgical planning and robotic-assisted minimally invasive surgery. This paper presents a new methodology for modelling of soft tissue deformation based on reaction-diffusion mechanics via neural dynamics. The po...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 56; no. 12; pp. 2163 - 2177 |
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| Autores principales: | , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Dec2018
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=133056259&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 133056259 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Dec2018 vid: 56 iid: 12 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 133056259 133056259 NLM29845488 10.1007/s11517-018-1849-5 NLM29845488 133056259 ppf: 2163 ppct: 14 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Soft tissue deformation modelling through neural dynamics-based reaction-diffusion mechanics. aug: au: Zhang, Jinao Zhong, Yongmin Gu, Chengfan affil: School of Engineering, RMIT University, 3083, Bundoora, VIC, Australia sug: subj: Models, Anatomic Connective Tissue Physiology Connective Tissue Anatomy and Histology Neural Networks (Computer) Phantoms, Imaging Kinematics Computer Simulation Feedback Diffusion ab: Soft tissue deformation modelling forms the basis of development of surgical simulation, surgical planning and robotic-assisted minimally invasive surgery. This paper presents a new methodology for modelling of soft tissue deformation based on reaction-diffusion mechanics via neural dynamics. The potential energy stored in soft tissues due to a mechanical load to deform tissues away from their rest state is treated as the equivalent transmembrane potential energy, and it is distributed in the tissue masses in the manner of reaction-diffusion propagation of nonlinear electrical waves. The reaction-diffusion propagation of mechanical potential energy and nonrigid mechanics of motion are combined to model soft tissue deformation and its dynamics, both of which are further formulated as the dynamics of cellular neural networks to achieve real-time computational performance. The proposed methodology is implemented with a haptic device for interactive soft tissue deformation with force feedback. Experimental results demonstrate that the proposed methodology exhibits nonlinear force-displacement relationship for nonlinear soft tissue deformation. Homogeneous, anisotropic and heterogeneous soft tissue material properties can be modelled through the inherent physical properties of mass points. Graphical abstract Soft tissue deformation modelling with haptic feedback via neural dynamics-based reaction-diffusion mechanics. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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