Abstract High Order Tensor (HOT) diffusion magnetic resonance imaging is an important method to reveal the microstructural information of living brain white matter. However, its time-consuming data acquisition and low fiber reconstructing resolution limit its clinical application.In this paper, a fiber orientation estimation method with weighted sparse is presented based on HOT model. Firstly, the HOT spherical deconvolution model for fiber orientation estimation is established. Then, a sparse representation method of fiber orientation is put forward. Finally, a l1-norm optimization model is built for the sparse constraint deconvolution. A computing method of applying the training results of sparse dictionary with lower order into the high-order problem is proposed to achieve the solution of the optimization problem. The experimental results on simulated and vivo data show that the fiber orientation estimation method improves the angular resolution of HOT tensor imaging method and reduces the angle recognition error.
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2015, Vol. 28 
