A Unified Approach for Spatial and Angular Super-Resolution of Diffusion Tensor MRI

摘要：

　　Diffusion magnetic resonance imaging(dMRI)can provide quantitative information with which to visualize and study connectivity and continuity of neural pathways in nervous systems.However,the very subtle regions and multiple intra-voxel orientations of water diffusion in brain cannnot accurately be represented in low spatial resolution imaging with tensor model.Yet,the ability to trace and describe such regions is critical for some applications such as neurosurgery and pathologic diagnosis.In this paper,we proposed a new single image acquisition superresolution method to increase both the spatial and angular resolution of dMRI.The proposed approach called single dMRI super-resolution reconstruction with compressed sensing(SSR-CS),uses a low number of single diffusion MRI in different gradients.This acquisition scheme is effectively in reducing acquisition time while improving the signal-tonoise ratio(SNR).The proposed method combines the two strategies of nonlocal similarity reconstruction and compressed sensing reconstruction in a sparse basis of spherical ridgelets to reconstruct high resolution image in k-space with complex orientations.The split Bregman approach is introduced for solving the SSR-CS problem.The performance of the proposed method is quantitatively evaluated on simulated diffusion MRI,using both spatial and angular reconstruction evaluating indexes.We also compared our method with some other dMRI super resolution methods.

关键词： Diffusion magnetic resonance imaging (dMRI) Tensor model Single dMRI super-resolution Compressed sensing (CS) Sparse representation

作者: Shi Yin Xinge You Weiyong Xue Bo Li Yue Zhao Xiao-Yuan Jing Patrick S.P.Wang Yuanyan Tang

作者单位: School of Electronic Information and Communications,Huazhong University of Science and Technology,Wu School of Computer,Wuhan University,Wuhan,China College of Computer and Information Science,Northeastern University,Boston,USA Faculty of Science and Technology,University of Macau,Macau,China

会议类型: 国际会议

会议名称: 第七届全国模式识别学术会议(The 7th Chinese Conference on Pattern Recognition,CCPR2016)

会议地点: 成都

会议语种:英文

页码: 312-324

在线出版日期: 2016-11-03（万方平台首次上网日期，不代表论文的发表时间）