Adjugate Diffusion Tensors for Geodesic Tractography in White Matter

作者：Fuster Andrea^*; Dela Haije Tom; Tristan Vega Antonio; Plantinga Birgit; Westin Carl Fredrik; Florack Luc

来源：Journal of Mathematical Imaging and Vision, 2016, 54(1): 1-14.

DOI：10.1007/s10851-015-0586-8

• Riemannian geometry
• Geodesic tractography
• Diffusion tensor imaging
• Brownian motion
• Diffusion generator
• Sharpened diffusion tensor

One of the approaches in diffusion tensor imaging is to consider a Riemannian metric given by the inverse diffusion tensor. Such a metric is used for geodesic tractography and connectivity analysis in white matter. We propose a metric tensor given by the adjugate rather than the previously proposed inverse diffusion tensor. The adjugate metric can also be employed in the sharpening framework. Tractography experiments on synthetic and real brain diffusion data show improvement for high-curvature tracts and in the vicinity of isotropic diffusion regions relative to most results for inverse (sharpened) diffusion tensors, and especially on real data. In addition, adjugate tensors are shown to be more robust to noise.

• 出版日期2016-1