Titlebook: Visualization and Processing of Tensor Fields; Advances and Perspec David Laidlaw,Joachim Weickert Book 2009 Springer-Verlag Berlin Heidelb

invade

T. H. J. M. Peeters,P. R. Rodrigues,A. Vilanova,B. M. ter Haar Romeny

BIBLE

T. J. Jankun-Kelly,Song Zhang,A. C. Callan-Jones,Robert A. Pelcovits,V. A. Slavin,David H. Laidlaw

破譯密碼

D. Sosa-Cabrera,M. A. Rodriguez-Florido,E. Suarez-Santana,Juan Ruiz-Alzola

rectum

A Mixture of Wisharts (MOW) Model for Multifiber Reconstructioncontinuousmixture of diffusion tensors. When the mixing distribution is a Wishart distribution, the Laplace transform yields a closed form expression. Additionally, we show that the traditional diffusion tensor model is a limiting case of this continuousmixture of tensors model. We then formulate th

Inordinate

Tensor Glyph Warping: Visualizing Metric Tensor Fields using Riemannian Exponential Mapsy solving the eikonal equation, a nonlinear partial differential equation (PDE), or it can be derived analytically for some manifolds. To avoid heavy calculations, we also include first- and second-order Taylor approximations to exp and log. In our experiments, these are shown to be sufficiently acc

Misnomer

A General Structure Tensor Concept and Coherence-Enhancing Diffusion Filtering for Matrix Fieldselds that relies on the operator-algebraic properties of symmetric matrices, rather than their channel-wise treatment of earlier proposals..Numerical experiments with artificial and real DT-MRI data confirm the gap-closing and flow-enhancing qualities of the technique presented.

white-matter

Coordinates-Based Diffusion Over the Space of Symmetric Positive-Definite Matrices., the space of n × n symmetric matrices. The “image” is described here as a section of a fiber bundle. Then, the metric over P. is combined with the metric over the twoor three-dimensional image domain in order to form the metric over the section. By means of the Beltrami framework, we define a fun

似少年

Modelling, Fitting and Sampling in Diffusion MRIements and designing acquisition schemes that provide the best estimates of model parameters. We construct a simple geometric model of white-matter tissue and derive an expression that relates the model parameters to the diffusion MRI signal.The axon density and diameter are parameters of the model

廢止

實(shí)現(xiàn)

A Mixture of Wisharts (MOW) Model for Multifiber Reconstructionoscopic scale in vivo. By producing quantitative data on the motion of water molecules that naturally occurs in brain tissues as part of the physical diffusion process, DW-MRI can be used to map the fiber paths in the brain white matter. Estimatingthe local complex architecture in the presence of in