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《Journal of Zhejiang University(Engineering Science)》 2014-06
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Fiber reconstruction algorithm based on discrete spherical deconvolution

LI Zhi-juan;FENG Yuan-jing;NIU Yan-peng;LI Rong;YE Feng;College of Information Engineering,Zhejiang University of Technology;  
In order to resolve the problem that the tracking process based on diffision tensor imaging(DTI)has difficulty in describing the complex fiber structure of the brain white matter,a deterministic tracking algorithm based on discrete spherical deconvolution was proposed.The algorithm uses discrete fiber orientation density function to build the spherical deconvolution model,which aims at relieving the dependence on the continuous spherical function model and getting high angular resolution identification.A spherical Gaussian function was used to make up for the discretization error,then the streamline tracking algorithm was implemented on the basis of the aboving model.Experimental results concluded from the synthetic data,platform data and real clinical data demonstrate that the proposed model evidently improves the resolution of small angle crossing fibers within voxel,meanwhile the noise is effectively restrained.Compared with the reconstruction algorithms based on other models,the proposed algorithm can reflect the true connection of brain neural tissue in vivo more accurately.
【Fund】: 国家自然科学基金资助项目(61379020);; 钱江人才计划资助项目(2012R10051);; 浙江省自然科学基金资助项目(Y13F030056)
【CateGory Index】: TP391.41
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