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Embedded Finite Elements for Modeling Axonal Injury.
Garimella, Harsha T; Menghani, Ritika R; Gerber, Jesse I; Sridhar, Srikumar; Kraft, Reuben H.
Afiliación
  • Garimella HT; Department of Mechanical and Nuclear Engineering, The Pennsylvania State University, University Park, 16801, USA.
  • Menghani RR; Computational Medicine and Biology Division, CFD Research Corporation, 701 McMillian Way NW, Huntsville, AL, 35806, USA.
  • Gerber JI; Department of Mechanical and Nuclear Engineering, The Pennsylvania State University, University Park, 16801, USA.
  • Sridhar S; Department of Mechanical and Nuclear Engineering, The Pennsylvania State University, University Park, 16801, USA.
  • Kraft RH; Department of Computer Science and Engineering, The Pennsylvania State University, University Park, 16801, USA.
Ann Biomed Eng ; 47(9): 1889-1907, 2019 Sep.
Article en En | MEDLINE | ID: mdl-30519759
ABSTRACT
The purpose of this paper is to propose and develop a large strain embedded finite element formulation that can be used to explicitly model axonal fiber bundle tractography from diffusion tensor imaging of the brain. Once incorporated, the fibers offer the capability to monitor tract-level strains that give insight into the biomechanics of brain injury. We show that one commercial software has a volume and mass redundancy issue when including embedded axonal fiber and that a newly developed algorithm is able to correct this discrepancy. We provide a validation analysis for stress and energy to demonstrate the method.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Axones / Lesiones Encefálicas / Análisis de Elementos Finitos / Modelos Biológicos Límite: Humans Idioma: En Revista: Ann Biomed Eng Año: 2019 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Axones / Lesiones Encefálicas / Análisis de Elementos Finitos / Modelos Biológicos Límite: Humans Idioma: En Revista: Ann Biomed Eng Año: 2019 Tipo del documento: Article País de afiliación: Estados Unidos
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