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Frontiers Abstracts

Workflow For Creating a Simulation Ready Virtual Population For Finite Element Modeling

[+] Author and Article Information
Kerim O. Genc

Simpleware Ltd.,
22575 Leanne Ter. #346,
Ashburn, VA
e-mail: k.genc@simpleware.com

Paul Segars

Duke University,
2424 Erwin Rd.,
Durham, NC
e-mail: paul.segars@duke.edu

Steve Cockram

Simpleware Ltd.,
Bradninch Hall Castle St.,
Exeter EX4 3PL, UK
e-mail: s.cockram@simpleware.com

Dane Thompson

ANSYS Inc.,
2645 Zanker Rd.,
San Jose, CA
e-mail: dane.thompson@ansys.com

Marc Horner

ANSYS Inc.,
1007 Church St.,
Evanston, IL
e-mail: marc.horner@ansys.com

Ross Cotton

e-mail: r.cotton@simpleware.com

Philippe Young

e-mail: p.young@simpleware.com
Simpleware Ltd.,
Bradninch Hall Castle St.,
Exeter EX4 3PL, UK

Manuscript received October 1, 2013; final manuscript received October 18, 2013; published online December 5, 2013. Assoc. Editor: Brad Davis.

J. Med. Devices 7(4), 040926 (Dec 05, 2013) (2 pages) Paper No: MED-13-1247; doi: 10.1115/1.4025847 History: Received October 01, 2013; Revised October 18, 2013

Three dimensional image-based meshing of multipart structures from medical scan data continues to reveal exciting new possibilities for the application of simulation techniques to a wide range of biomedical problems. However, significant challenges to creating a population of simulation compatible models still exist. These include: 1) dataset availability—due to privacy rules and cost, very few readily available dataset repositories of human phantoms exist; 2) segmentation difficulty—segmentation of scan datasets is extremely man-hour intensive. Effort is often measured by months to years for a single model; 3) clean CAD model extraction—the faceted volumetric meshes and CAD geometry must contain conformal face mapping between touching objects. Since traditional part-by-part meshing approaches risk gaps or overlap between adjacent parts, manual and time consuming repair may be required. This paper demonstrates a potential solution to these challenges through a fast and efficient workflow that begins with newly available anatomical geometries, and culminates in a solved multi-object computational simulation. Using the new series of 4D extended cardiac-torso (XCAT) phantoms created by Segars et al., we use ScanIP (Simpleware Ltd., Exeter, UK) to convert these datasets into multi-object simulation ready geometry files that are imported into HFSS (ANSYS Inc., Canonsburg, PA) for EM simulation and analysis.

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References

Figures

Grahic Jump Location
Fig. 1

Reconstruction (one of seven models) of the soft tissues (left), muscle/bone (middle) and a visualization of the solved HFSS model (right)

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