DocumentCode :
1791871
Title :
A physical model identification method of soft tissue deformation for virtual surgery
Author :
Tian Wang ; Fang Zhao ; Wei Gao ; Xiufen Ye ; Donghua Yu ; Yang Gao
Author_Institution :
Coll. of Autom., Harbin Eng. Univ., Harbin, China
fYear :
2014
fDate :
3-6 Aug. 2014
Firstpage :
298
Lastpage :
302
Abstract :
This paper studied the virtual surgery of soft tissue modeling. Due to today´s theory modeling and computer simulation results cannot reflect the mechanics and deformation properties of soft tissues accurately, this paper proposed least squares support vector machines (LSSVM) method to establish model between force and deformation by obtaining experimental results. Compared with the experimental results, the identification results of the identified model of LSSVM obtains well performance in terms of projection curve and standard deviation (MSE =0.4847). The results show that the LSSVM method is useful and valid.
Keywords :
least squares approximations; medical computing; support vector machines; surgery; virtual reality; LSSVM method; MSE; least squares support vector machines; physical model identification method; projection curve; soft tissue deformation; standard deviation; virtual surgery; Biological tissues; Computational modeling; Deformable models; Numerical models; Skin; Solid modeling; Surgery; Identified Model; LSSVM; Soft tissue modeling; Virtual surgery;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mechatronics and Automation (ICMA), 2014 IEEE International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-1-4799-3978-7
Type :
conf
DOI :
10.1109/ICMA.2014.6885712
Filename :
6885712
Link To Document :
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