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使用超二次曲面标记可视化张量场。

Visualization of tensor fields using superquadric glyphs.

作者信息

Ennis Daniel B, Kindlman Gordon, Rodriguez Ignacio, Helm Patrick A, McVeigh Elliot R

机构信息

National Institutes of Health, National Heart, Lung, and Blood Institute, Bethesda, Maryland, USA.

出版信息

Magn Reson Med. 2005 Jan;53(1):169-76. doi: 10.1002/mrm.20318.

Abstract

The spatially varying tensor fields that arise in magnetic resonance imaging are difficult to visualize due to the multivariate nature of the data. To improve the understanding of myocardial structure and function a family of objects called glyphs, derived from superquadric parametric functions, are used to create informative and intuitive visualizations of the tensor fields. The superquadric glyphs are used to visualize both diffusion and strain tensors obtained in canine myocardium. The eigensystem of each tensor defines the glyph shape and orientation. Superquadric functions provide a continuum of shapes across four distinct eigensystems (lambda(i), sorted eigenvalues), lambda(1) = lambda(2) = lambda(3) (spherical), lambda(1) < lambda(2) = lambda(3) (oblate), lambda(1) > lambda(2) = lambda(3) (prolate), and lambda(1) > lambda(2) > lambda(3) (cuboid). The superquadric glyphs are especially useful for identifying regions of anisotropic structure and function. Diffusion tensor renderings exhibit fiber angle trends and orthotropy (three distinct eigenvalues). Visualization of strain tensors with superquadric glyphs compactly exhibits radial thickening gradients, circumferential and longitudinal shortening, and torsion combined. The orthotropic nature of many biologic tissues and their DTMRI and strain data require visualization strategies that clearly exhibit the anisotropy of the data if it is to be interpreted properly. Superquadric glyphs improve the ability to distinguish fiber orientation and tissue orthotropy compared to ellipsoids.

摘要

由于数据的多变量性质,磁共振成像中出现的空间变化张量场很难可视化。为了更好地理解心肌结构和功能,一族从超二次参数函数派生而来的称为象形图的对象被用于创建张量场的信息丰富且直观的可视化。超二次象形图用于可视化在犬心肌中获得的扩散张量和应变张量。每个张量的特征系统定义了象形图的形状和方向。超二次函数在四个不同的特征系统(λ(i),排序后的特征值)中提供了连续的形状,λ(1)=λ(2)=λ(3)(球形),λ(1)<λ(2)=λ(3)(扁球形),λ(1)>λ(2)=λ(3)(长球形),以及λ(1)>λ(2)>λ(

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