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作 者:罗伶俐 王远军[1] LUO Ling-li;WANG Yuan-jun(Institute of Medical Imaging Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China)
机构地区:[1]上海理工大学医学影像工程研究所,上海200093
出 处:《小型微型计算机系统》2021年第2期374-380,共7页Journal of Chinese Computer Systems
基 金:国家自然科学基金项目(61201067)资助;上海市自然科学基金项目(18ZR1426900)资助.
摘 要:提升总体平均扩散传播算子(Ensemble Average diffusion Propagator,EAP)的重建精度一直以来都是扩散磁共振成像领域中扩散光谱成像(Diffusion Spectrum Imaging,DSI)的核心问题.在诸多成像算法中,用径向基函数(Radial Basis Function,RBF)作为扩散MR信号插值基函数的方法在纤维方向分布重建及成像统计标量重建方面均获得了理想的EAP重建效果,为进一步提升重建效率及精度,本文基于RBF方法提出了对信号进行自适应衰减建模的方法,并结合确保扩散张量正定性的张量求解算法,分别基于系数l1,l2正则化方法求解最优化参数以作对比.针对体模数据的实验结果显示,该算法在提升各项指标重建精度及计算效率方面均取得了理想效果.Improving the estimation accuracy of the Ensemble Average diffusion Propagator(EAP)has always been a core issue of diffusion spectrum imaging in the field of diffusion magnetic resonance imaging.Among many methods,the radial basis function(RBF)is used as the interpolation basis function for diffusion MR signal to obtain the ideal EAP reconstruction effect both in reconstruction of fiber orientation estimation and scalar statistics.In order to further improve the calculation efficiency and reconstruction accuracy,a method modeling the signal adaptive attenuation based on the RBF is proposed in this paper.The tensor estimating method ensuring the positive definiteness of the diffusion tensor is combined,and the optimization is performed by method based on l1 and l2 regularization respectively for comparison.Experimental results about phantom data show that the algorithm has achieved ideal results in terms of improving the reconstruction accuracy of various indicators and calculation efficiency.
分 类 号:TP391[自动化与计算机技术—计算机应用技术]
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