DocumentCode :
3085276
Title :
Statistical finite element analysis
Author :
Khalaji, Iman ; Rahemifar, Kaamran ; Samani, Abbas
Author_Institution :
Electrical Engineering Department, University of Western Ontario, London, N6A5B9 Canada
fYear :
2008
fDate :
20-25 Aug. 2008
Firstpage :
5577
Lastpage :
5580
Abstract :
A novel technique is introduced for tissue deformation and stress analysis. Compared to the conventional Finite Element method, this technique is orders of magnitude faster and yet still very accurate. The proposed technique uses preprocessed data obtained from FE analyses of a number of similar objects in a Statistical Shape Model framework as described below. This technique takes advantage of the fact that the body organs have limited variability, especially in terms of their geometry. As such, it is well suited for calculating tissue displacements of body organs. The proposed technique can be applied in many biomedical applications such as image guided surgery, or virtual reality environment development where tissue behavior is simulated for training purposes.
Keywords :
Biological system modeling; Computational modeling; Deformable models; Finite element methods; Geometry; Medical simulation; Shape; Stress; Surgery; Virtual reality; Algorithms; Computer Simulation; Elastic Modulus; Finite Element Analysis; Models, Biological; Models, Statistical; Pattern Recognition, Automated; Viscera; Viscosity;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, 2008. EMBS 2008. 30th Annual International Conference of the IEEE
Conference_Location :
Vancouver, BC
ISSN :
1557-170X
Print_ISBN :
978-1-4244-1814-5
Electronic_ISBN :
1557-170X
Type :
conf
DOI :
10.1109/IEMBS.2008.4650478
Filename :
4650478
Link To Document :
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