p-version of the finite-element method for highly heterogeneous simulation of human bone

Müller-Karger, Carmen; Rank, Ernst; Cerrolaza, M.

doi:10.1016/s0168-874x(03)00113-6

Cited by 14 publications

(9 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Shapiro et al [30], [2] generated inverse distance weighing interpolation with R-function and distance fields. Shin et al [19] proposed representation scheme FGM as an analogy to constructive solid geometry (CSG) scheme of solid modeling. Kumar et al [10], [42] proposed a set based approach with separate sets representing geometry model and attribute model respectively.…”

Section: Heterogeneous Human Body Modelingmentioning

confidence: 99%

“…For analysis of bone, the heterogeneity of cortical and cancellous bone is commonly accounted for by considering several sets of elastic modulus for bone material [4]. Muller et al [19] developed a three dimensional heterogeneous model of the human tibia for finite element analysis. Recently Cheng et al proposed heterogeneous solid representation scheme based on material feature [6].…”

Section: Heterogeneous Human Body Modelingmentioning

confidence: 99%

“…Although some researchers presented theoretical directions for heterogeneous bio-modeling [19], [6] and others represented bio-object as a composite [16], such model has not been reported in practice to our knowledge. In order to analyze human body as a whole for biomedical applications, the need of an analytical heterogeneous model is felt acutely.…”

Section: Heterogeneous Human Body Modelingmentioning

confidence: 99%

See 2 more Smart Citations

Reverse Engineering of Human Body: A B-spline based Heterogeneous Modeling Approach

Bhatt¹,

Warkhedkar²

2008

Computer-Aided Design and Applications

View full text Add to dashboard Cite

Human body is a natural heterogeneous object optimized in its structure and composition by natural processes over the years of evolution. In this paper, B-spline surface representation method is extended to represent material composition for the development of heterogeneous human body model. Two different approaches namely surface fairing and surface fit are used to create slice by slice model from CT scan data. Both the approaches are compared for different regression parameters. This methodology has potential to represent body internal details accurately with fewer digital input data and is extendable to 3-D solid modeling of human body with applications in FEM analysis, freeform-fabrication and tissue engineering.

show abstract

Section: Heterogeneous Human Body Modelingmentioning

confidence: 99%

Section: Heterogeneous Human Body Modelingmentioning

confidence: 99%

Section: Heterogeneous Human Body Modelingmentioning

confidence: 99%

See 1 more Smart Citation

Reverse Engineering of Human Body: A B-spline based Heterogeneous Modeling Approach

Bhatt¹,

Warkhedkar²

2008

Computer-Aided Design and Applications

View full text Add to dashboard Cite

show abstract

“…A possible solution lies in assigning each integration point the average value of the stiffness corresponding to the surrounding pixels. Nevertheless the size of this influence area is not univocally defined, Müller-Karger et al (2004).…”

Section: Introductionmentioning

confidence: 99%

Direct medical image-based Finite Element modelling for patient-specific simulation of future implants

Giovannelli

Ródenas

Navarro‐Jiménez

et al. 2017

Finite Elements in Analysis and Design

View full text Add to dashboard Cite

show abstract

Section: Introductionmentioning

confidence: 99%

Direct creation of patient-specific Finite Element models from medical images and preoperative prosthetic implant simulation using h-adaptive Cartesian grids.

Giovannelli¹

View full text Add to dashboard Cite

In silico medicine is believed to be one of the most disruptive changes in the near future. A great effort has been carried out during the last decade to develop predicting computational models to increase the diagnostic capabilities of medical doctors and the effectiveness of therapies. One of the key points of this revolution, will be personalisation, which means in most of the cases creating patient specific computational models, also called digital twins. This practice is currently widespread in research and there are quite a few software products in the market to obtain models from images. Nevertheless, in order to be usable in the clinical practice, these methods have to drastically reduce the time and human intervention required for the creation of the numerical models. First of all, I would like to thank my supervisors Prof. Juan José Ródenas and Dr. Manuel Tur for their exceptional support, trust and comprehension during these years. They actually offered me more dedication and guidance than I would have ever expected to receive. My special thanks go to Prof. Stéphane Bordas and Dr. Pierre Kerfriden for letting me be part of the Advanced Materials and Computational Mechanics research group and to the wonderful people I had the pleasure to meet during my stay at Cardiff University. I am also extremely grateful to Prof. Waldir Roque and Prof. Jessica Zhang for their hospitality and the insightful time dedicated. I would also like to extend my gratitude to all the members of the Departamento de Ingeniería Mechánica y Materiales at the Universitat Politècnica de València who never hesitated to offer me their experience, knowledge and help. In particular I would like to thank Prof.

show abstract

p-version of the finite-element method for highly heterogeneous simulation of human bone

Cited by 14 publications

References 13 publications

Reverse Engineering of Human Body: A B-spline based Heterogeneous Modeling Approach

Reverse Engineering of Human Body: A B-spline based Heterogeneous Modeling Approach

Direct medical image-based Finite Element modelling for patient-specific simulation of future implants

Direct creation of patient-specific Finite Element models from medical images and preoperative prosthetic implant simulation using h-adaptive Cartesian grids.

Contact Info

Product

Resources

About