TY - GEN
T1 - Material properties estimation of layered soft tissue based on MR observation and iterative FE simulation
AU - Tada, Mitsunori
AU - Nagai, Noritaka
AU - Maeno, Takashi
N1 - Copyright:
Copyright 2011 Elsevier B.V., All rights reserved.
PY - 2005
Y1 - 2005
N2 - In order to calculate deformation of soft tissue under arbitrary loading conditions, we have to take both non-linear material characteristics and subcutaneous structures into considerations. The estimation method of material properties presented in this paper accounts for these issues. It employs a compression test inside MRI in order to visualize deformation of hypodermic layered structure of living tissue, and an FE model of the compressed tissue in which non-linear material model is assigned. The FE analysis is iterated with updated material constant until the difference between the displacement field observed from MR images and calculated by FEM is minimized. The presented method has been applied to a 3-layered silicon rubber phantom. The results show the excellent performance of our method. The accuracy of the estimation is better than 15 %, and the reproducibility of the deformation is better than 0.4 mm even for an FE analysis with different boundary condition.
AB - In order to calculate deformation of soft tissue under arbitrary loading conditions, we have to take both non-linear material characteristics and subcutaneous structures into considerations. The estimation method of material properties presented in this paper accounts for these issues. It employs a compression test inside MRI in order to visualize deformation of hypodermic layered structure of living tissue, and an FE model of the compressed tissue in which non-linear material model is assigned. The FE analysis is iterated with updated material constant until the difference between the displacement field observed from MR images and calculated by FEM is minimized. The presented method has been applied to a 3-layered silicon rubber phantom. The results show the excellent performance of our method. The accuracy of the estimation is better than 15 %, and the reproducibility of the deformation is better than 0.4 mm even for an FE analysis with different boundary condition.
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U2 - 10.1007/11566489_78
DO - 10.1007/11566489_78
M3 - Conference contribution
C2 - 16686013
AN - SCOPUS:33744779931
SN - 3540293264
SN - 9783540293262
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 633
EP - 640
BT - Medical Image Computing and Computer-Assisted Intervention - MICCAI 2005 - 8th International Conference, Proceedings
T2 - 8th International Conference on Medical Image Computing and Computer-Assisted Intervention - MICCAI 2005
Y2 - 26 October 2005 through 29 October 2005
ER -