A review of diffusion tensor magnetic resonance imaging computational methods and software tools

Computers in Biology and Medicine

Volumn 41, Issue 12, 2011, Pages 1062-1072

  Hasan, Khader M ^a   Walimuni, Indika S ^a   Abid, Humaira ^a   Hahn, Klaus R ^b  

^a UNIVERSITY OF TEXAS MEDICAL SCHOOL   (United States)

^b INSTITUTE OF EPIDEMIOLOGY   (Germany)

Author keywords

AFNI; Atlas; Brain mapping; Connectivity; Diffusion kurtosis; Diffusion spectrum imaging; Diffusion tensor imaging; DKI; DSI; DTI; DTI software; FreeSurfer; FSL; HYDI; ICBM; Q ball; Quantification; Segmentation; SPM; TBSS; Tractography; VBA

Indexed keywords

BRAIN MAPPING; COMPUTER SOFTWARE; DIFFUSION; IMAGE SEGMENTATION; MAGNETIC RESONANCE IMAGING; TENSORS;

AFNI; ATLAS; CONNECTIVITY; DIFFUSION SPECTRUM IMAGING; FREESURFER; HYDI; ICBM; Q-BALLS; QUANTIFICATION; TBSS; TRACTOGRAPHY;

DIFFUSION TENSOR IMAGING;

COMPUTER PROGRAM; DIFFUSION TENSOR IMAGING; DIFFUSION WEIGHTED IMAGING; HUMAN; IMAGE ANALYSIS; IMAGE PROCESSING; MATHEMATICAL MODEL; PRIORITY JOURNAL; REVIEW;

EID: 79960280880     PISSN: 00104825     EISSN: 18790534     Source Type: Journal    
DOI: 10.1016/j.compbiomed.2010.10.008     Document Type: Article

References (150)

1. Basser P.J. New histological and physiological stains derived from diffusion-tensor MR images. Ann. NY Acad. Sci. 1997, 820:123-138. (Review).
2. Basser P.J., Mattiello J., Le Bihan D. Estimation of the effective self diffusion tensor from NMR spin echo. J. Magn. Reson. B 1994, 123:247-254.
3. Le Bihan D., Mangin J.F., Poupon C., Clark C., Pappata S., Molko N., Chabriat H. Diffusion tensor imaging: concepts and applications. J. Magn. Reson. Imaging 2001, 13:534-546.
4. Le Bihan D. Looking into the functional architecture of the brain with diffusion MRI. Nat. Rev. Neurosci. 2003, 4:469-480.
5. Basser P.J., Jones D.K. Diffusion-tensor MRI: theory, experimental design and data analysis-a technical review. NMR Biomed. 2002, 15:456-467.
6. Mori S., Zhang J. Principles of diffusion tensor imaging and its applications to basic neuroscience research. Neuron 2006, 51:527-539.
7. Beaulieu C. The basis of anisotropic water diffusion in the nervous system-a technical review. NMR Biomed. 2002, 15:435-455. (Review).
8. Pierpaoli C., Jezzard P., Basser P.J., Barnett A., Di Chiro G. Diffusion tensor MR imaging of the human brain. Radiology 1996, 201:637-648.
9. Le Bihan D., Breton E., Lallemand D., Grenier P., Cabanis E., Laval-Jeantet M. MR imaging of intravoxel incoherent motions: application to diffusion and perfusion in neurologic disorders. Radiology 1986, 161:401-407.
10. Fieremans E., De Deene Y., Delputte S., Ozdemir M.S., D'Asseler Y., Vlassenbroeck J., Deblaere K., Achten E., Lemahieu I. Simulation and experimental verification of the diffusion in an anisotropic fiber phantom. J. Magn. Reson. 2008, 190:189-199.
11. Le Bihan D. Looking into the functional architecture of the brain with diffusion MRI. Nat. Rev. Neurosci. 2003, 4(6):469-480. (Review).
12. Mori S. Introduction to Diffusion Tensor Imaging 2007, Elsevier, Amsterdam.
13. Johansen-Berg H., Behrens T.E.J. Diffusion MRI: From Quantitative Measurements to In Vivo Neuroanatomy 2009, Academic Press, London.
14. Westin C.F., Maier S.E., Magmata H., Nabavi A., Jolesz F.A., Kikinis R. Processing and visualization for diffusion tensor MRI. Med. Image Anal. 2002, 6:93-108. (Review).
15. Hagmann P., Jonasson L., Maeder P., Thiran J.P., Wedeen V.J., Meuli R. Understanding diffusion MR imaging techniques: from scalar diffusion-weighted imaging to diffusion tensor imaging and beyond. Radiographics 2006, 26:S205-S223.
16. Hasan K.M. Fundamentals of diffusion tensor imaging of the entire human brain: review of basic theory, data acquisition, processing and potential applications at 1.5T and 3.0T. Progress in Brain Mapping Research 2006, 1-80. Nova Science Publishers, Hauppauge, NY, (Chapter 1). F.J. Chen (Ed.).
17. Minati L., Weglarz W.P. Physical foundations, models, and methods of diffusion magnetic resonance imaging of the brain: a review. Concepts Magn. Reson. A 2007, 30A:278-307.
18. Lenglet C., Campbell J.S., Descoteaux M., Haro G., Savadjiev P., Wassermann D., Anwander A., Deriche R., Pike G.B., Sapiro G., Siddiqi K., Thompson P.M. Mathematical methods for diffusion MRI processing. Neuroimage 2009, 45:S111-S122.
19. Alexander A.L., Lee J.E., Lazar M., Field A.S. Diffusion tensor imaging of the brain. Neurotherapeutics 2007, 4:316-329. (Review).
20. Kreher B.W., Schneider J.F., Mader I., Martin E., Hening J., Llyasov K.A. Multitensor approach for analysis and tracking of complex fiber configurations. Magn. Reson. Med. 2005, 54:1216-1225.
21. Liu C., Bammer R., Moseley M.E. Limitations of apparent diffusion coefficient-based models in characterizing non-Gaussian diffusion. Magn. Reson. Med. 2005, 54:419-428.
22. Peled S., Friman O., Jolesz F., Westin C.F. Geometrically constrained two-tensor model for crossing tracts in DWI. Magn. Reson. Imaging 2006, 24:1263-1270.
23. Yamada K., Sakai K., Hoogenraad F.G., Holthuizen R., Akazawa K., Ito H., Oouchi H., Matsushima S., Kubota T., Sasajima H., Mineura K., Nishimura T. Multitensor tractography enables better depiction of motor pathways: initial clinical experience using diffusion-weighted MR imaging with standard b-value. AJNR-Am. J. Neuroradiol. 2007, 28:1668-1673.
24. Ramirez-Manzanares A., Rivera M., Vemuri B.C., Carney P., Mareci T. Diffusion basis functions decomposition for estimating white matter intravoxel fiber geometry. IEEE Trans. Med. Imaging 2007, 26:1091-1102.
25. Sotiropoulos S.N., Bai L., Morgan P.S., Auer D.P., Constantinescu C.S., Tench C.R. A regularized two-tensor model fit to low angular resolution diffusion images using basis directions. J. Magn. Reson. Imaging 2008, 28:199-209.
26. Kabasawa H., Masutani Y., Abe O., Aoki S., Ohtomo K. Quantitative diffusion tensor analysis using multiple tensor ellipsoids model and tensor field interpolation at fiber crossing. Acad. Radiol. 2008, 15:84-92.
27. Landman B.A., Wan H., Bogovic J.A., Bazin P.L., Prince J.L. Resolution of crossing fibers with constrained compressed sensing using traditional diffusion tensor MRI. Proc. Soc. Photo Opt. Instrum. Eng. 2010, 7623:76231H.
28. Özarslan E., Mareci T.H. Generalized diffusion tensor imaging and analytical relationships between diffusion tensor imaging and high angular resolution diffusion imaging. Magn. Reson. Med. 2003, 50:955-965.
29. Liu C., Bammer R., Acar B., Moseley M.E. Characterizing non-Gaussian diffusion by using generalized diffusion tensors. Magn. Reson. Med. 2004, 51:924-937.
30. Akkerman E.M. The direct tensor solution and higher-order acquisition schemes for generalized diffusion tensor imaging. J. Magn. Reson. 2010, 206:9-19.
31. Xing D., Papadakis N.G., Huang C.L., Lee V.M., Carpenter T.A., Hall L.D. Optimised diffusion-weighting for measurement of apparent diffusion coefficient (ADC) in human brain. Magn. Reson. Imaging 1997, 15:771-784.
32. Jones D.K., Horsfield M.A., Simmons A. Optimal strategies for measuring diffusion in anisotropic systems by magnetic resonance imaging. Magn. Reson. Med. 1999, 42:515-525.
33. Papadakis N.G., Xing D., Huang C.L., Hall L.D., Carpenter T.A. A comparative study of acquisition schemes for diffusion tensor imaging using MRI. J. Magn. Reson. 1999, 137:67-82.
34. Skare S., Hedehus M., Moseley M.E., Li T.Q. Condition number as a measure of noise performance of diffusion tensor data acquisition schemes with MRI. J. Magn. Reson. 2000, 147:340-352.
35. Hasan K.M., Parker D.L., Alexander A.L. Comparison of gradient encoding schemes for diffusion-tensor MRI. J. Magn. Reson. Imaging 2001, 13:769-780.
36. Batchelor P.G., Atkinson D., Hill D.L.G., Calamante F., Connelly A. Anisotropic noise propagation in diffusion tensor MRI sampling schemes. Magn. Reson. Med. 2003, 49:1143-1151.
37. Alexander D.C., Barker G.J. Optimal imaging parameters for fiber-orientation estimation in diffusion MRI. Neuroimage 2005, 27:357-367.
38. Mang S.C., Gembris D., Grodd W., Klose U. Comparison of gradient encoding directions for higher order tensor diffusion data. Magn. Reson. Med. 2009, 61:335-343.
39. Farrell J.A., Landman B.A., Jones C.K., Smith S.A., Prince J.L., van Zijl P.C., Mori S. Effects of signal-to-noise ratio on the accuracy and reproducibility of diffusion tensor imaging-derived fractional anisotropy, mean diffusivity, and principal eigenvector measurements at 1.5T. J. Magn. Reson. Imaging 2007, 26:756-767.
40. Landman B.A., Farrell J.A., Jones C.K., Smith S.A., Prince J.L., Mori S. Effects of diffusion weighting schemes on the reproducibility of dti-derived fractional anisotropy, mean diffusivity, and principal eigenvector measurements at 1.5T. Neuroimage 2007, 36:1123-1138.
41. Hasan K.M. A framework for quality control and parameter optimization in diffusion tensor imaging: theoretical analysis and validation. Magn. Reson. Imaging 2007, 25:1196-1202.
42. Zhan L., Leow A.D., Jahanshad N., Chiang M.C., Barysheva M., Lee A.D., Toga A.W., McMahon K.L., de Zubicaray G.I., Wright M.J., Thompson P.M. How does angular resolution affect diffusion imaging measures?. Neuroimage 2010, 49:1357-1371.
43. Ni H., Kavcic V., Zhu T., Ekholm S., Zhong J. Effects of number of diffusion gradient directions on derived diffusion tensor imaging indices in human brain. AJNR-Am. J. Neuroradiol. 2006, 27:1776-1781.
44. Peng H., Arfanakis K. Diffusion tensor encoding schemes optimized for white matter fibers with selected orientations. Magn. Reson. Imaging 2007, 25:147-153.
45. Jensen J.H., Helpern J.A., Ramani A., Lu H., Kaczynski K. Diffusional kurtosis imaging: the quantification of non-Gaussian water diffusion by means of magnetic resonance imaging. Magn. Reson. Med. 2005, 53:1432-1440.
46. Jensen J.H., Helpern J.A. MRI quantification of non-Gaussian water diffusion by kurtosis analysis. NMR Biomed. 2010, 10.1002/nbm.1518.
47. Papadakis N.G., Zheng Y., Wilkinson I.D. Analysis of diffusion tensor magnetic resonance imaging data using principal component analysis. Phys. Med. Biol. 2003, 48:343-350.
48. Arfanakis K., Cordes D., Haughton V.M., Carew J.D., Meyerand M.E. Independent component analysis applied to diffusion tensor MRI. Magn. Reson. Med. 2002, 47:354-363.
49. Akkerman E.M. Efficient measurement and calculation of MR diffusion anisotropy images using the Platonic variance method. Magn. Reson. Med. 2003, 49:599-604.
50. Hasan K.M., Narayana P.A. Computation of the fractional anisotropy and mean diffusivity maps without tensor decoding and diagonalization: theoretical analysis and validation. Magn. Reson. Med. 2003, 50:589-598.
51. Maier S.E., Vajapeyam S., Mamata H., Westin C.F., Jolesz F.A., Mulkern R.V. Biexponential diffusion tensor analysis of human brain diffusion data. Magn. Reson. Med. 2004, 51:321-330.
52. Clark C.A., Hedehus M., Moseley M.E. In vivo mapping of the fast and slow diffusion tensors in human brain. Magn. Reson. Med. 2002, 47:623-628.
53. Inglis B.A., Bossart E.L., Buckley D.L., Wirth E.D., Mareci T.H. Visualization of neural tissue water compartments using biexponential diffusion tensor MRI. Magn. Reson. Med. 2001, 45:580-587.
54. Wiegell M.R., Larsson H.B., Wedeen V.J. Fiber crossing in human brain depicted with diffusion tensor MR imaging. Radiology 2000, 217:897-903.
55. Alexander D.C., Barker G.J., Arridge S.R. Detection and modeling of non-Gaussian apparent diffusion coefficient profiles in human brain data. Magn. Reson. Med. 2002, 48:331-340.
56. Staempfli P., Jaermann T., Crelier G.R., Kollias S., Valavanis A., Boesiger P. Resolving fiber crossing using advanced fast marching tractography based on diffusion tensor imaging. Neuroimage 2006, 30:110-120.
57. Alexander D.C. Multiple-fiber reconstruction algorithms for diffusion MRI. Ann. NY Acad. Sci. 2005, 1064:113-133. (Review).
58. Frank L.R. Anisotropy in high angular resolution diffusion-weighted MRI. Magn. Reson. Med. 2001, 45:935-939.
59. Frank L.R. Characterization of anisotropy in high angular resolution diffusion-weighted MRI. Magn. Reson. Med. 2002, 47:1083-1099.
60. Alexander D.C., Barker G.J., Arridge S.R. Detection and modelling of non-Gaussian apparent diffusion coefficient profiles in human brain data. Magn. Reson. Med. 2002, 48:331-340.
61. Tuch D.S., Reese T.G., Wiegell M.R., Makris N., Belliveau J.W., Wedeen V.J. High angular resolution diffusion imaging reveals intravoxel white matter fiber heterogeneity. Magn. Reson. Med. 2002, 48:577-582.
62. Tournier J.D., Calamante F., Gadian D.G., Connelly A. Direct estimation of the fiber orientation density function from diffusion-weighted MRI data using sphericalde convolution. Neuroimage 2004, 23:1176-1185.
63. Jian B., Vemuri B.C. A unified computational framework for deconvolution to reconstruct multiple fibers from diffusion weighted MRI. IEEE Trans. Med. Imaging 2007, 26:1464-1471.
64. Minat L., Aquino D., Rampoldi S., Papa S., Grisoli M., Bruzzone M.G., Maccagnano E. Biexponential and diffusional kurtosis imaging, and generalised diffusion-tensor imaging (GDTI) with rank-4 tensors: a study in a group of healthy subjects. J. Magn. Magn. Mater. 2007, 20:241-253.
65. Tuch D.S. Q-ball imaging. Magn. Reson. Med. 2004, 52:1358-1372.
66. Tuch D.S., Reese T.G., Wiegell M.R., Wedeen V.J. Diffusion MRI of complex neural architecture. Neuron 2003, 40:885-895.
67. Barnett A. Theory of Q-ball imaging redux: implications for fiber tracking. Magn. Reson. Med. 2009, 62:910-923.
68. Wedeen V.J., Wang R.P., Schmahmann J.D., Benner T., Tseng W.Y., Dai G., Pandya D.N., Agmann P.H., Arceuil H.D., de Crespigny A.J. Diffusion spectrum magnetic resonance imaging (DSI) tractography of crossing fibers. Neuroimage 2008, 41:1267-1277.
69. Wedeen V.J., Hagmann P., Tseng W.Y., Reese T.G., Weisskoff R.M. Mapping complex tissue architecture with diffusion spectrum magnetic resonance imaging. Magn. Reson. Med. 2005, 54:1377-1386.
70. Kuo L.W., Chen J.H., Wedeen V.J., Tseng W.Y. Optimization of diffusion spectrum imaging and q-ball imaging on clinical MRI system. Neuroimage 2008, 41:7-18.
71. Schmahmann J.D., Pandya D.N., Wang R., Dai G., D'Arceuil H.E., de Crespigny A.J., Wedeen V.J. Association fibre pathways of the brain: parallel observations from diffusion spectrum imaging and autoradiography. Brain 2007, 130:630-653.
72. Granziera C., Schmahmann J.D., Hadjikhani N., Meyer H., Meuli R., Wedeen V., Krueger G. Diffusion spectrum imaging shows the structural basis of functional cerebellar circuits in the human cerebellum in vivo. PLoS One 2009, 4:e5101.
73. Takahashi E., Dai G., Wang R., Ohki K., Rosen G.D., Galaburda A.M., Grant P.E., Wedeen V.J. Development of cerebral fiber pathways in cats revealed by diffusion spectrum imaging. Neuroimage 2010, 49:1231-1240.
74. Nezamzadeh M., Wedeen V.J., Wang R., Zhang Y., Zhan W., Young K., Meyerhoff D.J., Weiner M.W., Schuff N. In-vivo investigation of the human cingulum bundle using the optimization of MR diffusion spectrum imaging. Eur. J. Radiol. 2010, 75:e29-e36.
75. Alexander A.L., Wu Y.C., Venkat P.C. Hybrid diffusion imaging (HYDI). Conf. Proc. IEEE Eng. Med. Biol. Soc. 2006, 1:2245-2248.
76. Jaermann T., Crelier G., Pruessmann K.P., Golay X., Netsch T., van Muiswinkel A.M., Mori S., van Zijl P.C., Valavanis A., Kollias S., Boesiger P. SENSE-DTI at 3T. Magn. Reson. Med. 2004, 51:230-236.
77. Roebroeck A., Galuske R., Formisano E., Chiry O., Bratzke H., Ronen I., Kim D.S., Goebel R. High-resolution diffusion tensor imaging and tractography of the human optic chiasm at 9.4T. Neuroimage 2008, 39:157-168.
78. Mukerjee P., Hess C.P., Xu D., Han E.T., Kelley D.A., Vigneron D.B. Development and initial evaluation of 7-T q-ball imaging of the human brain. Magn. Reson. Imaging 2008, 26:171-180.
79. Jaermann T., De Zanche N., Staempfli P., Pruessmann K.P., Valavanis A., Boesiger P.P., Kollias S.S. Preliminary experience with visualization of intracortical fibers by focused high-resolution diffusion tensor imaging. AJNR-Am. J. Neuroradiol. 2008, 29:146-150.
80. Hasan K.M., Kamali A., Kramer L.A. Mapping the human brain white matter tracts relative to cortical and deep gray matter using diffusion tensor imaging at high spatial resolution. Magn. Reson. Imaging 2009, 27:631-636.
81. Hasan K.M., Basser P.J., Parker D.L., Alexander A.L. Analytical computation of the eigenvalues and eigenvectors in DT-MRI. J. Magn. Reson. 2001, 152:41-47.
82. Mori S., Wakana S., Nagae-Poetscher L.M., van Zijl P.C.M. MRI Atlas of Human White Matter 2005, Elsevier.
83. Conturo T.E., Lori N.F., Cull T.S., Akbudak E., Snyder A.Z., Shimony J.S., McKinstry R.C., Burton H., Raichle M.E. Tracking neuronal fiber pathways in the living human brain. Proc. Natl. Acad. Sci. USA 1999, 18:10422-10427.
84. Mori S., van Zijl P.C. Fiber tracking: principles and strategies-a technical review. NMR Biomed. 2002, 15:468-480. (Review).
85. Catani M., Howard R.J., Pajevic S., Jones D.K. Virtual in vivo interactive dissection of white matter fasciculi in the human brain. Neuroimage 2002, 17:77-94.
86. Wakana S., Jiang H., Nagae-Poetscher L.M., van Zijl P.C., Mori S. Fiber tract-based atlas of human white matter anatomy. Radiology 2004, 230:77-87.
87. Aralasmak A., Ulmer J.L., Kocak M., Salvan C.V., Hillis A.E., Yousem D.M. Association, commissural, and projection pathways and their functional deficit reported in literature. J. Comput. Assist. Tomogr. 2006, 30:695-715. (Review).
88. Wakana S., Caprihan A., Panzenboeck M.M., Fallon J.H., Perry M., Gollub R.L., Hua K., Zhang J., Jiang H., Dubey P., Blitz A., van Zijl P.C., Mori S. Reproducibility of quantitative tractography methods applied to cerebral white matter. Neuroimage 2007, 36:630-644.
89. Hasan K.M., Kamali A., Abid H., Kramer L.A., Fletcher J.M., Ewing-Cobbs L. Quantification of the spatiotemporal micro structural organization of the human brain association, projection and commissural pathways across the lifespan using diffusion tensor tractography. Brain Struct. Funct. 2010, 214:361-373.
90. Hasan K.M., Iftikhar A., Kamali A., Kramer L.A., Ashtari M., Cirino P.T., Papanicolaou A.C., Fletcher J.M., Ewing-Cobbs L. Development and aging of the healthy human brain uncinate fasciculus across the lifespan using diffusion tensor tractography. Brain Res. 2009, 1276:67-76.
91. Hasan K.M., Kamali A., Iftikhar A., Kramer L.A., Papanicolaou A.C., Fletcher J.M., Ewing-Cobbs L. Diffusion tensor tractography quantification of the human corpus callosum fiber pathways across the lifespan. Brain Res. 2009, 1249:91-100.
92. Anderson A.W. Theoretical analysis of the effects of noise on diffusion tensor imaging. Magn. Reson. Med. 2001, 46:1174-1188.
93. Mamata H., Jolesz F.A., Maier S.E. Characterization of central nervous system structures by magnetic resonance diffusion anisotropy. Neurochem. Int. 2004, 45:553-560.
94. Oouchi H., Yamada K., Sakai K., Kizu O., Kubota T., Ito H., Nishimura T. Diffusion anisotropy measurement of brain white matter is affected by voxel size: underestimation occurs in areas with crossing fibers. AJNR-Am. J. Neuroradiol. 2007, 28:1102-1116.
95. Jiang H., van Zijl P.C., Kim J., Pearlson G.D., Mori S. DtiStudio: resource program for diffusion tensor computation and fiber bundle tracking. Comput. Methods Programs Biomed. 2006, 81:106-116.
96. P.A. Cook, Y. Bai, S. Nedjati-Gilani, K.K. Seunarine, M.G. Hall, G.J. Parker, D.C. Alexander, Camino: open-source diffusion-MRI reconstruction and processing, in: Proceedings of the 14th Scientific Meeting of the International Society for Magnetic Resonance in Medicine, Seattle, WA, USA, May 2006, p. 2759.
97. Smith S.M., Jenkinson M., Woolrich M.W., Beckmann C.F., Behrens T.E., Johansen-Berg H., Bannister P.R., De Luca M., Drobnjak I., Flitney D.E., Niazy R.K., Saunders J., Vickers J., Zhang Y., De Stefano N., Brady J.M., Matthews P.M. Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage 2004, 23:S208-S219. (Review).
98. Ashburner L. Computational anatomy with the SPM software. Magn. Reson. Imaging 2009, 27:1163-1174.
99. Fischl B., Salat D.H., Busa E., Albert M., Dieterich M., Haselgrove C., van der Kouwe A., Killiany R., Kennedy D., Klaveness S., Montillo A., Makris N., Rosen B., Dale A.M. Whole brain segmentation: automated labeling of neuro anatomical structures in the human brain. Neuron 2002, 33:341-355.
100. Cox R.W. AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. Comput. Biomed. Res. 1996, 29:162-173.
101. Lucas B.C., Bogovic J.A., Carass A., Bazin P.L., Prince J.L., Pham D.L., Landman B.A. The Java Image Science Toolkit (JIST) for rapid prototyping and publishing of neuroimaging software. Neuroinformatics 2010, 8:5-17. (Erratum in: Neuroinformatics 8 (2010) 19.
102. Cárdenes R., Muñoz-Moreno E., Tristan-Vega A., Martin-Fernandez M. Saturn: a software application of tensor utilities for research in neuroimaging. Comput. Methods Programs Biomed. 2010, 97:264-279.
103. Y. Cointepas, C. Poupon, R. Maroy, D. Rivieỳre, D. LeBihan, J.F. Mangin, A freely available Anatomist/BrainVISA package for analysis of diffusion MR data, in: Proceedings of the Ninth HBM Scientific Meeting, New York; Neuroimage 19 (2003) 810 〈〉. http://brainvisainfo.
104. Karmonik C., York M., Grossman R., Kakkar E., Patel K., Haykal H., King D. An image analysis pipeline for the semi-automated analysis of clinical fMRI images based on freely available software. Comput. Biol. Med. 2010, 40(3):279-287.
105. Chang L.C., Jones D.K., Pierpaoli C. RESTORE: robust estimation of tensors by outlier rejection. Magn. Reson. Med. 2005, 53:1088-1095.
106. Leemans A., Jones D.K. The B-matrix must be rotated when correcting for subject motion in DTI data. Magn. Reson. Med. 2009, 61:1336-1349.
107. Klein A., Andersson J., Ardekani B.A., Ashburner J., Avants B., Chiang M.C., Christensen G.E., Collins D.L., Gee J., Hellier P., Song J.H., Jenkinson M., Lepage C., Rueckert D., Thompson P., Vercauteren T., Woods R.P., Mann J.J., Parsey R.V. Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration. Neuroimage 2009, 46:786-802.
108. Shen D., Davatzikos C. HAMMER: Hierarchical attribute matching mechanism for elastic registration. IEEE Trans. Med. Imaging 2002, 21:1421-1439.
109. Andersson J.L.R., Skare S. A model-based method for retrospective correction of geometric distortions in diffusion-weighted EPI. Neuroimage 2002, 16:177-199.
110. Ardekani S., Sinha U. Geometric distortion correction of high-resolution 3T diffusion tensor brain images. Magn. Reson. Med. 2005, 54:1163-1171.
111. Netsch T., van Muiswinkel A. Quantitative evaluation of image-based distortion correction in diffusion tensor imaging. IEEE Trans. Med. Imaging 2004, 23:789-798.
112. Smith S.M. Fast robust automated brain extraction. Hum. Brain Mapp. 2002, 17:143-155.
113. Ding Z., Gore J.C., Anderson A.W. Reduction of noise in diffusion tensor images using anisotropic smoothing. Magn. Reson. Med. 2005, 53:485-490.
114. Hahn K.R., Prigarin S., Rodenacker K., Hasan K.M. Denoising for diffusion tensor imaging with low signal to noise ratios: method and Monte Carlo validation. Int. J. Biostatist. Biomath. 2010, 1:63-81.
115. Jones D.K., Griffin L.D., Alexander D.C., Catani M., Horsfield M.A., Howard R., Williams S.C. Spatial normalization and averaging of diffusion tensor MRI data sets. Neuroimage 2002, 17:592-617.
116. Jones D.K., Symms M.R., Cercignani M., Howard R.J. The effect of filter size on VBM analyses of DT-MRI data. Neuroimage 2005, 26:546-554.
117. Salat D.H., Tuch D.S., Greve D.N., van der Kouwe A.J., Hevelone N.D., Zaleta A.K., Rosen B.R., Fischl B., Corkin S., Rosas H.D., Dale A.M. Age-related alterations in white matter microstructure measured by diffusion tensor imaging. Neurobiol. Aging 2005, 26:1215-1227.
118. Snook L., Plewes C., Beaulieu C. Voxel based versus region of interest analysis in diffusion tensor imaging of neurodevelopment. Neuroimage 2007, 34:243-252.
119. Ashtari M., Cervellione K., Cottone J., Ardekani B.A., Sevy S., Kumra S. Diffusion abnormalities in adolescents and young adults with a history of heavy cannabis use. J. Psychiatr. Res. 2009, 43:189-204.
120. Vangberg T.R., Skranes J., Dale A.M., Martinussen M., Brubakk A.M., Haraldseth O. Changes in white matter diffusion anisotropy in adolescents born prematurely. Neuroimage 2006, 32:1538-1548.
121. Keller T.A., Just M.A. Altering cortical connectivity: remediation-induced changes in the white matter of poor readers. Neuron 2009, 64:624-631.
122. Smith S.M., Jenkinson M., Johansen-Berg H., Rueckert D., Nichols T.E., Mackay C.E., Watkins K.E., Ciccarelli O., Cader M.Z., Matthews P.M., Behrens T.E. Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. Neuroimage 2006, 31:1487-1505.
123. Smith S.M., Johansen-Berg H., Jenkinson M., Rueckert D., Nichols T.E., Miller K.L., Robson M.D., Jones D.K., Klein J.C., Bartsch A.J., Behrens T.E. Acquisition and voxelwise analysis of multi-subject diffusion data with tract-based spatial statistics. Nat. Protoc. 2007, 2:499-503.
124. Focke N.K., Yogarajah M., Bonelli S.B., Bartlett P.A., Symms M.R., Duncan J.S. Voxel-based diffusion tensor imaging in patients with mesial temporal lobe epilepsy and hippocampal sclerosis. Neuroimage 2008, 40:728-737.
125. Abe O., Takao H., Gonoi W., Sasaki H., Murakami M., Kabasawa H., Kawaguchi H., Goto M., Yamada H., Yamasue H., Kasai K., Aoki S., Ohtomo K. Voxel-based analysis of the diffusion tensor. Neuroradiology 2010, 52:699-710.
126. Alexander D.C., Pierpaoli C., Basser P.J., Gee J.C. Spatial transformations of diffusion tensor magnetic resonance images. IEEE Trans. Med. Imaging 2001, 20:1131-1139.
127. Xu D., Mori S., Shen D., van Zijl P.C., Davatzikos C. Spatial normalization of diffusion tensor fields. Magn. Reson. Med. 2003, 50:175-182.
128. Peng H., Orlichenko A., Dawe R.J., Agam G., Zhang S., Arfanakis K. Development of a human brain diffusion tensor template. Neuroimage 2009, 46:967-980.
129. Kamali A., Kramer L.A., Hasan K.M. Feasibility of prefronto-caudate pathway tractography using high resolution diffusion tensor tractography data at 3T. J. Neurosci. Methods 2010, 191:249-254.
130. Yamamoto T., Yamada K., Nishimura T., Kinoshita S. Tractography to depict three layers of visual field trajectories to the calcarine gyri. Am. J. Ophthalmol. 2005, 140:781-785.
131. Hua K., Zhang J., Wakana S., Jiang H., Li X., Reich D.S., Calabresi P.A., Pekar J.J., van Zijl P.C., Mori S. Tract probability maps in stereotaxic spaces: analyses of white matter anatomy and tract-specific quantification. Neuroimage 2008, 39:336-347.
132. Zhang Y., Zhang J., Oishi K., Faria A.V., Jiang H., Li X., Akhter K., Rosa-Neto P., Pike G.B., Evans A., Toga A.W., Woods R., Mazziotta J.C., Miller M.I., van Zijl P.C., Mori S. Atlas-guided tract reconstruction for automated and comprehensive examination of the white matter anatomy. Neuroimage 2010, 52:1289-1301.
133. Faria A.V., Zhang J., Oishi K., Li X., Jiang H., Akhter K., Hermoye L., Lee S.K., Hoon A., Stashinko E., Miller M.I., van Zijl P.C., Mori S. Atlas-based analysis of neurodevelopment from infancy to adulthood using diffusion tensor imaging and applications for automated abnormality detection. Neuroimage 2010, 52:415-428.
134. Lawes I.N., Barrick T.R., Murugam V., Spierings N., Evans D.R., Song M., Clark C.A. Atlas-based segmentation of white matter tracts of the human brain using diffusion tensor tractography and comparison with classical dissection. Neuroimage 2008, 39:62-79.
135. Mori S., Oishi K., Jiang H., Jiang L., Li X., Akhter K., Hua K., Faria A.V., Mahmood A., Woods R., Toga A.W., Pike G.B., Neto P.R., Evans A., Zhang J., Huang H., Miller M.I., van Zijl P., Mazziotta J. Stereotaxic white matter atlas based on diffusion tensor imaging in an ICBM template. Neuroimage 2008, 40:570-582.
136. Hagler D.J., Ahmadi M.E., Kuperman J., Holland D., McDonald C.R., Halgren E., Dale A.M. Automated white-matter tractography using probabilistic diffusion tensor atlas: application temporal lobe epilepsy. Hum. Brain Mapp. 2009, 30:1535-1547.
137. Verhoeven J.S., Sage C.A., Leemans A., Van Hecke W., Callaert D., Peeters R., De Cock P., Lagae P.L., Sunaert S. Construction of a stereotaxic DTI atlas with full diffusion tensor information for studying white matter maturation from childhood to adolescence using tractography-based segmentations. Hum. Brain Mapp. 2010, 31:470-486.
138. Hasan K.M., Frye R.E. Diffusion tensor based regional gray matter tissue segmentation using the international consortium for brain mapping atlases. Hum. Brain Mapp. 2010, 10.1002/hbm.21004.
139. Parker G.J.M., Haroon H.A., Wheeler-Kingshott C.A.M. A framework for a streamline-based Probabilistic Index of Connectivity (PICo) using a structural interpretation of MRI diffusion measurements. J. Magn. Reson. Imaging 2003, 18:242-254.
140. Parker G.J.M., Alexander D.C. Probabilistic anatomical connectivity derived from the microscopic persistent angular structure of cerebral tissue. Philos. Trans. R. Soc. B-Biol. Sci. 2005, 360:893-902.
141. Park H.J., Kim J.J., Lee S.K., Seok J.H., Chun J., Kim D.I., Lee J.D. Corpus callosal connection mapping using cortical gray matter parcellation and DT-MRI. Hum. Brain Mapp. 2008, 29:503-516.
142. Pannek K., Mathias J.L., Bigler E.D., Brown G., Taylor J.D., Rose S. An automated strategy for the delineation and parcellation of commissural pathways suitable for clinical populations utilising high angular resolution diffusion imaging tractography. Neuroimage 2010, 50:1044-1053.
143. Behrens. T.E., Johansen-Berg H., Woolrich M.W., Smith S.M., Wheeler-Kingshott C.A., Boulby P.A., Barker G.J., Sillery E.L., Sheehan K., Ciccarelli O., Thompson A.J., Brady J.M., Matthews P.M. Non-invasive mapping of connections between human thalamus and cortex using diffusion imaging. Nat. Neurosci. 2003, 6:750-757.
144. Zhang D., Snyder A.Z., Shimony J.S., Fox M.D., Raichle M.E. Noninvasive functional and structural connectivity mapping of the human thalamocortical system. Cereb. Cortex 2010, 20:1187-1194.
145. Helmich R.C., Derikx L.C., Bakker M., Scheeringa R., Bloem B.R., Toni I. Spatial remapping of cortico-striatal connectivity in Parkinson's disease. Cereb. Cortex 2010, 20:1175-1186.
146. Studholme C. Dense feature deformation morphometry: Incorporating DTI data into conventional MRI morphometry. Med. Image Anal. 2008, 12:742-751.
147. Staempfli P., Reischauer C., Jaermann T., Valavanis A., Kollias S., Boesiger P. Combining fMRI and DTI: a framework for exploring the limits of fMRI-guided DTI fiber tracking and for verifying DTI-based fiber tractography results. Neuroimage 2008, 39:119-126.
148. Inoue K., Ito H., Uchida S., Taki Y., Kinomura S., Tsuji I., Sato S., Horie K., Kawashima R., Ito M., Fukuda H. Decrease in glucose metabolism in frontal cortex associated with deterioration of microstructure of corpus callosum measured by diffusion tensor imaging in healthy elderly. Hum. Brain Mapp. 2008, 29:375-384.
149. Boss A., Kolb A., Hofmann M., Bisdas S., Nägele T., Ernemann U., Stegger L., Rossi C., Schlemmer H.P., Fannenberg C.P., Reimold M., Claussen C.D., Pichler B.J., Klose U. Diffusion tensor imaging in a human PET/MR hybrid system. Invest. Radiol. 2010, 45:270-274.
150. Hasan K.M., Walimuni I.S., Kramer L.A., Frye R.E. Human brain atlas-based volumetry and relaxometry: application to healthy development and natural aging. Magn. Reson. Med. 2010, 64(5):1382-1389.