Abstract
This paper introduces the meshfree reproducing kernel particle method for 3D image-based modelling of skeletal muscles. This approach allows for construction of simulation model based on pixel data obtained from medical images. The material properties and muscle fibre direction obtained from diffusion tensor imaging (DTI) are input at each pixel point. The reproducing kernel approximation allows a representation of material heterogeneity with smooth transition. A multiphase multichannel level set based segmentation framework is adopted for individual muscle segmentation using magnetic resonance images and DTI. The application of the proposed methods for modelling the human lower leg is demonstrated.
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