Keywords: Machine Learning/Artificial Intelligence, Diffusion Tensor ImagingDeep learning methods have been demonstrated state-of-the-art performance in Diffusion Magnetic Resonance Imaging (dMRI) denoising and parameter estimation. However, existing deep learning methods for dMRI are limited to the specific acquisition scheme. To solve the limitation, we proposed to use spherical harmonic coefficients as the deep learning network’s input. Our results have shown that the proposed method has a high performance in denoising and parameter estimation for DTI with a strong generalization ability.
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