A framework for facial surgery simulation

Koch, R; Roth, Samuel Hans Martin; Groß, Markus; Zimmermann, Albrecht; Sailer, Hermann F.

doi:10.1145/584458.584464

Cited by 37 publications

(23 citation statements)

References 19 publications

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“…Whereas the first works were based on discrete models such as mass-spring models (Delingette et al, 1994 ;Waters, 1996 ;Keeve et al, 1996 ;Teschner et al, 1999 ;Barré et al, 2000), many continuous Finite Element models were then proposed in the literature (Koch et al, 1996 ;Keeve et al, 1998 ;Koch et al, 1999 ;Zachow et al, 2000 ;Gladilin et al, 2001 ;Teschner, 2001 ;Chabanas et al, 2003 ;Mollemans et al, 2007).…”

Section: 2mentioning

confidence: 99%

Soft Tissue Finite Element Modeling and Calibration of the Material Properties in the Context of Computer-Assisted Medical Interventions

Payan

2016

Material Parameter Identification and Inverse Problems in Soft Tissue Biomechanics

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International audienceThis chapter aims at illustrating how patient-specific models of human organs / soft tissues can be implemented into Finite Element (FE) packages. First is addressed the question of the generation of patient-specific FE models compatible with the clinical constraints. Then is discussed the calibration of the material properties, with choices that should be done between calibrations based on ex vivo or in vivo tissues loadings. The example of computer assisted maxillofacial surgery is addressed and results based on patients' data are provided

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Section: 2mentioning

confidence: 99%

Soft Tissue Finite Element Modeling and Calibration of the Material Properties in the Context of Computer-Assisted Medical Interventions

Payan

2016

Material Parameter Identification and Inverse Problems in Soft Tissue Biomechanics

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“…Such applications -among many others include 3D face recognition and authentication [1][2][3], simulation of plastic facial surgery [4], facial expression simulation [5], facial animation [6] and facial morphing [7]. The challenge in developing the facial model is not only to have a model that looks real, but one which also can be efficiently utilized for the specific purpose for which the geometry is created.…”

Section: Introductionmentioning

confidence: 99%

Reconstruction of 3D Human Facial Images Using Partial Differential Equations

Elyan¹,

Ugail²

2007

JCP

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Abstract-One of the challenging problems in geometric modeling and computer graphics is the construction of realistic human facial geometry.Such geometry are essential for a wide range of applications, such as 3D face recognition, virtual reality applications, facial expression simulation and computer based plastic surgery application. This paper addresses a method for the construction of 3D geometry of human faces based on the use of Elliptic Partial Differential Equations (PDE). Here the geometry corresponding to a human face is treated as a set of surface patches, whereby each surface patch is represented using four boundary curves in the 3-space that formulate the appropriate boundary conditions for the chosen PDE. These boundary curves are extracted automatically using 3D data of human faces obtained using a 3D scanner. The solution of the PDE generates a continuous single surface patch describing the geometry of the original scanned data. In this study, through a number of experimental verifications we have shown the efficiency of the PDE based method for 3D facial surface reconstruction using scan data. In addition to this, we also show that our approach provides an efficient way of facial representation using a small set of parameters that could be utilized for efficient facial data storage and verification purposes.

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“…The medical prototype applications considered in GEMSS include maxillo-facial surgery simulation 23) , neuro-surgery support 36) , radiosurgery planning 16) , inhaled drug-delivery simulation 24) , cardio-vascular simulation 25) and advanced image reconstruction 3) . At the core of these bio-medical simulation applications are computationally demanding methods such as parallel Finite Element Modeling, parallel Computational Fluid Dynamics and parallel…”

Section: §1 Introductionmentioning

confidence: 99%

End-to-End QoS Support for a Medical Grid Service Infrastructure

et al. 2007

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Quality of Service support is an important prerequisite for the adoption of Grid technologies for medical applications. The GEMSS Grid infrastructure addressed this issue by offering end-to-end QoS in the form of explicit timeliness guarantees for compute-intensive medical simulation services. Within GEMSS, parallel applications installed on clusters or other HPC hardware may be exposed as QoS-aware Grid services for which clients may dynamically negotiate QoS constraints with respect to response time and price using Service Level Agreements. The GEMSS infrastructure and middleware is based on standard Web services technology and relies on a reservation based approach to QoS coupled with application specific performance models. In this paper we present an overview of the GEMSS infrastructure, describe the available QoS and security mechanisms, and demonstrate the effectiveness of our methods with a Grid-enabled medical imaging service.

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A framework for facial surgery simulation

Cited by 37 publications

References 19 publications

Soft Tissue Finite Element Modeling and Calibration of the Material Properties in the Context of Computer-Assisted Medical Interventions

Soft Tissue Finite Element Modeling and Calibration of the Material Properties in the Context of Computer-Assisted Medical Interventions

Reconstruction of 3D Human Facial Images Using Partial Differential Equations

End-to-End QoS Support for a Medical Grid Service Infrastructure

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