Study of Connectivity in the Brain Using the Full Diffusion Tensor from MRI

In this paper we propose a novel technique for the analysis of diffusion tensor magnetic resonance images. This method involves solving the full diffusion equation over a finite element mesh derived from the MR data. It calculates connection probabilities between points of interest, which can be compared within or between subjects. Unlike traditional tractography, we use all the data in the diffusion tensor at each voxel which is likely to increase robustness and make intersubject comparisons easier.

[1]  P. V. van Zijl,et al.  Three‐dimensional tracking of axonal projections in the brain by magnetic resonance imaging , 1999, Annals of neurology.

[2]  C. Nicholson,et al.  Extracellular space structure revealed by diffusion analysis , 1998, Trends in Neurosciences.

[3]  R. Turner,et al.  Diffusion MR imaging: clinical applications. , 1992, AJR. American journal of roentgenology.

[4]  P. Basser,et al.  A simplified method to measure the diffusion tensor from seven MR images , 1998, Magnetic resonance in medicine.

[5]  P. Basser,et al.  Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. , 1996, Journal of magnetic resonance. Series B.

[6]  M. I. Smith,et al.  A study of rotationally invariant and symmetric indices of diffusion anisotropy. , 1999, Magnetic resonance imaging.

[7]  James C. Gee,et al.  Elastic Matching of Diffusion Tensor Images , 2000, Comput. Vis. Image Underst..

[8]  S C Williams,et al.  Non‐invasive assessment of axonal fiber connectivity in the human brain via diffusion tensor MRI , 1999, Magnetic resonance in medicine.

[9]  Jamshid Dehmeshki,et al.  A fast marching analysis of MR diffusion tensor imaging for following white matter tracts. , 2000 .

[10]  J. Gore,et al.  Theoretical Model for Water Diffusion in Tissues , 1995, Magnetic resonance in medicine.

[11]  N. Papadakis,et al.  The reduction of the sorting bias in the eigenvalues of the diffusion tensor. , 1999, Magnetic resonance imaging.

[12]  M. Raichle,et al.  Tracking neuronal fiber pathways in the living human brain. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[13]  Haiying Liu,et al.  Investigation of intraoperative brain deformation using a 1.5-T interventional MR system: preliminary results , 1998, IEEE Transactions on Medical Imaging.

[14]  N. Papadakis,et al.  Minimal gradient encoding for robust estimation of diffusion anisotropy. , 2000, Magnetic resonance imaging.

[15]  P. Basser,et al.  Toward a quantitative assessment of diffusion anisotropy , 1996, Magnetic resonance in medicine.

[16]  E. Syková,et al.  Evolution of anisotropic diffusion in the developing rat corpus callosum. , 1997, Journal of neurophysiology.

[17]  Gordon L. Kindlmann,et al.  Strategies for Direct Volume Rendering of Diffusion Tensor Fields , 2000, IEEE Trans. Vis. Comput. Graph..

[18]  P. Basser,et al.  In vivo fiber tractography using DT‐MRI data , 2000, Magnetic resonance in medicine.

[19]  Daniel Rueckert,et al.  Assessment of Intraoperative Brain Deformation Using Interventional MR Imaging , 1999, MICCAI.

[20]  N G Papadakis,et al.  A comparative study of acquisition schemes for diffusion tensor imaging using MRI. , 1999, Journal of magnetic resonance.

[21]  M. Horsfield,et al.  Optimal strategies for measuring diffusion in anisotropic systems by magnetic resonance imaging , 1999, Magnetic resonance in medicine.

[22]  Tosio Kato.  Perturbation theory for linear operators , 1966 .

[23]  H. Langtangen.  Computational Partial Differential Equations , 1999 .