Least-square conformal brain mapping with spring energy

Least-square conformal brain mapping with spring energy

The human brain cortex is a highly convoluted sheet. Mapping of the cortical surface into a canonical coordinate space is an important tool for the study of the structure and function of the brain. Here, we present a technique based on least-square conformal mapping with spring energy for the mapping of the cortical surface. This method aims to reduce the metric and area distortion while mainta...

Optimization of Brain Conformal Mapping with Landmarks

To compare and integrate brain data, data from multiple subjects are typically mapped into a canonical space. One method to do this is to conformally map cortical surfaces to the sphere. It is well known that any genus zero Riemann surface can be conformally mapped to a sphere. Therefore, conformal mapping offers a convenient method to parameterize cortical surfaces without angular distortion, ...

Fast Least Square Matching

Least square matching (LSM) is one of the most accurate image matching methods in photogrammetry and remote sensing. The main disadvantage of the LSM is its high computational complexity due to large size of observation equations. To address this problem, in this paper a novel method, called fast least square matching (FLSM) is being presented. The main idea of the proposed FLSM is decreasing t...

Seepage with Nonlinear Permeability by Least Square FEM

In seepage problems, the coefficients of permeability in Laplace equation are usually assumed to be constant vs. both space and time; but in reality these coefficients are variable. In this study, the effect of material deformation due to external loads (consolidation) and variation of head in the consolidation process are considered. For the first case, formulation of kx and ky can be defined ...

Orthogonal Least Square with Boosting for Regression