Assaf Y, Pasternak O. Diffusion Tensor Imaging(DTI)-Based White Matter Mapping in Brain Research: A Review. Journal of Molecular Neuroscience, 2008, 34(1): 51-61
[2]
Basser P J, Mattiello J, LeBihan D. MR Diffusion Tensor Spectroscopy and Imaging. Biophysical Journal, 1994, 66(1): 259-267
[3]
Cheng J, Ghosh A, Deriche R, et al. Model-Free, Regularized, Fast, and Robust Analytical Orientation Distribution Function Estimation // Proc of the 13th Iternational Conference on Medical Image Computing and Computer-Assisted Intervention. Beijing, China, 2010: 648-656
[4]
Hlawitschka M, Scheuermann G. Tracking Lines in Higher Order Tensor Fields // Hagen H, ed. Scientific Visualization: Advanced Concepts. Dagstuhl, Germany: Schloss Dagstuhl, 2010: 124-135
[5]
zarslan E, Mareci T H. Generalized Diffusion Tensor Imaging and Analytical Relationships between Diffusion Tensor Imaging and High Angular Resolution Diffusion Imaging. Magnetic Resonance in Medicine, 2003, 50(5): 955-965
[6]
Moakher M. On the Averaging of Symmetric Positive-Definite Tensors. Journal of Elasticity, 2006, 82(3): 273-296
[7]
Moakher M, Norris A N. The Closest Elastic Tensor of Arbitrary Symmetry to an Elasticity Tensor of Lower Symmetry. Journal of Elasticity, 2006, 85(3): 215-263
[8]
Barmpoutis A, Hwang M S, Howland D, et al. Regularized Positive-Definite Fourth Order Tensor Field Estimation from DW-MRI. NeuroImage, 2009, 45(1): S153-S162
[9]
Barmpoutis A, Jeffery H, Vemuri B C. Approximating Symmetric Positive Semidefinite Tensors of Even Order. SIAM Journal on Imaging Sciences, 2012, 5(1): 434-464
[10]
Weldeselassie Y T, Barmpoutis A, Atkins M S. Symmetric Positive Semi-definite Cartesian Tensor Fiber Orientation Distributions(CT-FOD). Medical Image Analysis, 2012, 16(6): 1121-1129
[11]
Jeurissen B, Leemans A, Tournier J D, et al. Estimating the Number of Fiber Orientations in Diffusion MRI Voxels: A Constrained Spherical Deconvolution Study // Proc of the International Society for Magnetic Resonance in Medicine. Stockholm, Sweden, 2010: 573
[12]
Yeh F C, Tseng W Y I. Sparse Solution of Fiber Orientation Distribution Function by Diffusion Decomposition. PloS One, 2013. DOI: 10.1371/journal.pone.0075747
[13]
Merlet S, Caruyer E, Deriche R. Parametric Dictionary Learning for Modeling EAP and ODF in Diffusion MRI // Proc of the 15th International Conference on Medical Image Computing and Compu-ter-Assisted Intervention. Nice, France, 2012: 10-17
[14]
Donoho D L. Compressed Sensing. IEEE Trans on Information Theory, 2006, 52(4): 1289-1306
[15]
Candès E J, Romberg J, Tao T. Robust Uncertainty Principles: Exact Signal Reconstruction from Highly Incomplete Frequency Information. IEEE Trans on Information Theory, 2006, 52(2): 489-509
[16]
Anderson A W, Ding Z. Sub-voxel Measurement of Fiber Orientation Using High Angular Resolution Diffusion Tensor Imaging //Proc of the International Society for Magnetic Resonance in Medicine. Berkeley, USA, 2002: 440
[17]
Rudin W. Sums of Squares of Polynomials. The American Mathematical Monthly, 2000, 107(9): 813-821
[18]
Ghosh A, Tsigaridas E, Mourrain B, et al. A Polynomial App-roach for Extracting the Extrema of a Spherical Function and Its Application in Diffusion MRI. Medical Image Analysis, 2013, 17(5): 503-514
[19]
Patel V, Shi Y G, Thompson P M, et al. Mesh-Based Spherical Deconvolution: A Flexible Approach to Reconstruction of Non-negative Fiber Orientation Distributions. NeuroImage, 2010, 51(3): 1071-1081
[20]
Jiao F X, Gur Y, Johnson C R, et al. Detection of Crossing White Matter Fibers with High-Order Tensors and Rank-k Decompositions // Proc of the 22nd International Conference on Information Processing in Medical Imaging. Kloster Irsee, Germany, 2011: 538-549
[21]
Daducci A, Van de Ville D, Thiran J P, et al. Sparse Regularization for Fiber ODF Reconstruction: From the Suboptimality of 2 and 1 Priors to 0. Medical Image Analysis, 2014, 18(6): 820-833
[22]
Schultz T. Learning a Reliable Estimate of the Number of Fiber Directions in Diffusion MRI // Proc of the 15th International Conference on Medical Image Computing and Computer-Assisted Intervention. Nice, France, 2012: 493-500
[23]
Candès E J, Wakin M B, Boyd S P. Enhancing Sparsity by Reweighted 1 Minimization. Journal of Fourier Analysis and Applications, 2008, 14(5/6): 877-905
[24]
Tournier J D, Calamante F, Connelly A. Robust Determination of the Fibre Orientation Distribution in Diffusion MRI: Non-negativity Constrained Super-Resolved Spherical Deconvolution. NeuroImage, 2007, 35(4): 1459-1472
[25]
Tikhonov A N, Goncharsky A, Stepanov V V, et al. Numerical Methods for the Solution of Ill-Posed Problems. Dordrecht, The Netherlands: Springer-Science + Business Media, 1995
[26]
Parker G D, Marshall D, Rosin P L, et al. A Pitfall in the Reconstruction of Fibre ODFs Using Spherical Deconvolution of Diffusion MRI Data. NeuroImage, 2013, 65: 433-448
[27]
Sderman O, Jnsson B. Restricted Diffusion in Cylindrical Geometry. Journal of Magnetic Resonance: Series A, 1995, 117(1): 94-97
[28]
Malcolm J G, Shenton M E, Rathi Y. Filtered Multi-tensor Tractography. IEEE Trans on Medical Imaging, 2010, 29(9): 1664-1675
[29]
Li R, Feng J Y, Shao K L, et al. Higher Order Tensor Imaging Model Feature Extraction Algorithm Based on Iterative Search. China Journal of Biomedical Engineering, 2012, 31(3): 365-373 (in Chinese)(李 蓉,冯远静,邵开来,等.磁共振扩散高阶张量成像的脑白质纤维微结构模型及特征提取算法.中国生物医学工程学报, 2012, 31(3): 365-373)
