Monday, July 22, 2013

Finsler几何 由于度量未必是二次型,因此我们不能用正交标架,所以情形就变得困难。事实上,假如标架是正交的,活动标架导致的联络是度量相容的,解方程组总能使联络同时是无挠的,这就是Riemann几何上所发生的情形

Finsler Geometry on Higher Order Tensor Fields and Applications to High Angular Resolution Diffusion Imaging

AUTHOR(S)
Astola, Laura; Florack, Luc
PUB. DATE
May 2011
SOURCE
International Journal of Computer Vision;May2011, Vol. 92 Issue 3, p325
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
We study 3D-multidirectional images, using Finsler geometry. The application considered here is in medical image analysis, specifically in High Angular Resolution Diffusion Imaging (HARDI) (Tuch et al. in Magn. Reson. Med. 48(6):1358-1372, ) of the brain. The goal is to reveal the architecture of the neural fibers in brain white matter. To the variety of existing techniques, we wish to add novel approaches that exploit differential geometry and tensor calculus. In Diffusion Tensor Imaging (DTI), the diffusion of water is modeled by a symmetric positive definite second order tensor, leading naturally to a Riemannian geometric framework. A limitation is that it is based on the assumption that there exists a single dominant direction of fibers restricting the thermal motion of water molecules. Using HARDI data and higher order tensor models, we can extract multiple relevant directions, and Finsler geometry provides the natural geometric generalization appropriate for multi-fiber analysis. In this paper we provide an exact criterion to determine whether a spherical function satisfies the strong convexity criterion essential for a Finsler norm. We also show a novel fiber tracking method in Finsler setting. Our model incorporates a scale parameter, which can be beneficial in view of the noisy nature of the data. We demonstrate our methods on analytic as well as simulated and real HARDI data.
 

An Introduction to Riemann-Finsler Geometry - David Dai-Wai Bao / Shiing-Shen Chern / Zhongmin Shen

2013-03-04 21:47:00

 
 

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