The massive amount of nonstandard high-dimensional brain imaging data being generated is often difficult to analyze using current techniques. This challenge in brain image analysis requires new computational approaches and solutions. But none of the research papers or books in the field describe the quantitative techniques with detailed illustratio

chapter 1|20 pages

Introduction to Brain and Medical Images

chapter 2|8 pages

Bernoulli Models for Binary Images

chapter 3|22 pages

General Linear Models

chapter 4|16 pages

Gaussian Kernel Smoothing

chapter 5|18 pages

Random Fields Theory

chapter 6|16 pages

Anisotropic Kernel Smoothing

chapter 7|20 pages

Multivariate General Linear Models

chapter 8|28 pages

Cortical Surface Analysis

chapter 9|14 pages

Heat Kernel Smoothing on Surfaces

chapter 10|22 pages

Cosine Series Representation of 3D Curves

chapter 11|34 pages

Weighted Spherical Harmonic Representation

chapter 12|28 pages

Multivariate Surface Shape Analysis

chapter 14|20 pages

Persistent Homology

chapter 15|24 pages

Sparse Networks

chapter 16|16 pages

Sparse Shape Models

chapter 17|16 pages

Modeling Structural Brain Networks

chapter 18|12 pages

Mixed Effects Models