Local white matter geometry from diffusion tensor gradients

被引:16
作者
Savadjiev, Peter [1 ,2 ]
Kindlmann, Gordon L. [3 ,4 ]
Bouix, Sylvain [1 ]
Shenton, Martha E. [1 ,2 ,5 ]
Westin, Carl-Fredrik [2 ]
机构
[1] Harvard Univ, Brigham & Womens Hosp, Sch Med, Psychiat Neuroimaging Lab,Dept Psychiat, Boston, MA 02115 USA
[2] Harvard Univ, Brigham & Womens Hosp, Sch Med, Dept Radiol, Boston, MA 02115 USA
[3] Univ Chicago, Dept Comp Sci, Chicago, IL 60637 USA
[4] Univ Chicago, Computat Inst, Chicago, IL 60637 USA
[5] Harvard Univ, Sch Med, Neurosci Lab, Dept Psychiat,VA Boston Healthcare Syst, Brockton, MA 02401 USA
关键词
Diffusion tensor imaging; Magnetic resonance imaging; Fiber geometry; Rotation tangents; Fiber dispersion; Fiber curving; Schizophrenia; DT-MRI; SEGMENTATION; QUANTIFICATION; APPROXIMATION; FRAMEWORK;
D O I
10.1016/j.neuroimage.2009.10.073
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
We introduce a mathematical framework for computing geometrical properties of white matter fibers directly from diffusion tensor fields. The key idea is to isolate the portion of the gradient of the tensor field corresponding to local variation in tensor orientation, and to project it onto a coordinate frame of tensor eigenvectors. The resulting eigenframe-centered representation then makes it possible to define scalar indices (or measures) that describe the local white matter geometry directly from the diffusion tensor field and its gradient, without requiring prior tractography. We derive new scalar indices of (1) fiber dispersion and (2) fiber curving, and we demonstrate them on synthetic and in vivo data. Finally, we illustrate their applicability to a group study on schizophrenia. (C) 2009 Elsevier Inc. All rights reserved.
引用
收藏
页码:3175 / 3186
页数:12
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