FEM-based simulation of tumor growth in medical image

Shuqian Luo; Ying Nie

doi:10.1117/12.531008

5 May 2004 FEM-based simulation of tumor growth in medical image

Shuqian Luo, Ying Nie

Proceedings Volume 5367, Medical Imaging 2004: Visualization, Image-Guided Procedures, and Display; (2004) https://doi.org/10.1117/12.531008
Event: Medical Imaging 2004, 2004, San Diego, California, United States

Abstract

Brain model has found wide applications in areas including surgical-path planning, image-guided surgery systems, and virtual medical environments. In comparison with the modeling of normal brain anatomy, the modeling of anatomical abnormalities appears to be rather weak. Particularly, there are considerable differences between abnormal brain images and normal brain images, due to the growth of brain tumor. In order to find the correspondence between abnormal brain images and normal ones, it is necessary to make an estimation or simulation of the brain deformation. In this paper, a deformable model of brain tissue with both geometric and physical nonlinear properties based on finite element method is presented. It is assumed that the brain tissue are nonlinearly elastic solids obeying the equations of an incompressible nonlinearly elastics neo-Hookean model. we incorporate the physical inhomogeneous of brain tissue into our FEM model. The non-linearity of the model needs to solve the deformation of the model using an iteration method. The Updated Lagrange for iteration is used. To assure the convergence of iteration, we adopt the fixed arc length method. This model has advantages over those linear models in its more real tissue properties and its capability of simulating more serious brain deformation. The inclusion of second order displacement items into the balance and geometry functions allows for the estimation of more serious brain deformation. We referenced the model presented by Stelios K so as to ascertain the initial position of tumor as well as our tumor model definition. Furthermore, we expend it from 2-D to 3-D and simplify the calculation process.

Citation Download Citation

Shuqian Luo and Ying Nie "FEM-based simulation of tumor growth in medical image", Proc. SPIE 5367, Medical Imaging 2004: Visualization, Image-Guided Procedures, and Display, (5 May 2004); https://doi.org/10.1117/12.531008

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