MR image denoising method for brain surface 3D modeling

Abstract

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.

Keywords

Mean Square Error / Wavelet Coefficient / Peak Signal Noise Ratio / Wavelet Domain / Triangle Mesh

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This work has been supported by the National Natural Science Foundation of China (No.61202169), the Tianjin Key Natural Science Foundation (No.13JCZDJC34600), the China Scholarship Council (CSC) Foundation (No.201308120010), and the Training Plan of Tianjin University Innovation Team (No.TD12-5016).