Abstract
This paper introduces the meshfree Reproducing Kernel Particle Method (RKPM) in conjunction with a stabilized conforming nodal integration for 3D image-based modeling of skeletal muscles. This approach allows for construction of simulation model based on pixel data obtained from medical images. The model consists of different materials and muscle fiber direction obtained from Diffusion Tensor Imaging (DTI) is input at each pixel point. The reproducing kernel (RK) approximation also allows a representation of material heterogeneity with smooth transition. A multiphase multichannel level set based segmentation using Magnetic Resonance Images (MRI) and DTI formulated under a modified functional has been integrated into RKPM framework. The use of proposed methods for modeling the human lower leg is demonstrated.
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Basava, R.R. et al. (2014). Pixel Based Meshfree Modeling of Skeletal Muscles. In: Zhang, Y.J., Tavares, J.M.R.S. (eds) Computational Modeling of Objects Presented in Images. Fundamentals, Methods, and Applications. CompIMAGE 2014. Lecture Notes in Computer Science, vol 8641. Springer, Cham. https://doi.org/10.1007/978-3-319-09994-1_32
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DOI: https://doi.org/10.1007/978-3-319-09994-1_32
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