Three-dimensional(3D) modeling of medical images is a critical part of surgical simulation. In this paper, we focus on the magnetic resonance(MR) images denoising for brain modeling reconstruction, and exploit a practical solution. We attempt to remove the noise existing in the MR imaging signal and preserve the image characteristics. A wavelet-based adaptive curve shrinkage function is presented in spherical coordinates system. The comparative experiments show that the denoising method can preserve better image details and enhance the coefficients of contours. Using these denoised images, the brain 3D visualization is given through surface triangle mesh model, which demonstrates the effectiveness of the proposed method.
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Tianjin Key Laboratory of Intelligent Computing & Novel Software Technology, Key Laboratory of Computer Vision and System, Ministry of Education, Tianjin University of Technology;
机译:Reconstructing Population Density Surfaces from Areal Data: A Comparison of Tobler's Pycnophylactic Interpolation Method and Area-to-Point Kriging. 面状数据的人口密度面重构:Tobler’s Pycnophylactic 插值法和面到点克里金插值法的对比