An Introduction to Diffusion Tensor Image Analysis

Diffusion-tensor image registration

In this chapter, we introduce the problem of registering diffusion tensor magnetic resonance (DT-MR) images. The registration task for these images is made challenging by the orientational information they contain, which is affected by the registration transformation. This information about orientation and other aspects of the diffusion tensor are exploited in the development of similarity meas...

An Introduction to Computational Diffusion MRI: the Diffusion Tensor and Beyond

This chapter gives an introduction to the principles of diffusion magnetic resonance imaging (MRI) with emphasis on the computational aspects. It introduces the philosophies underlying the technique and shows how to sensitize MRI measurements to the motion of particles within a sample material. The main body of the chapter is a technical review of diffusion MRI reconstruction algorithms, which ...

Assessment of the Log-Euclidean Metric Performance in Diffusion Tensor Image Segmentation

Introduction: Appropriate definition of the distance measure between diffusion tensors has a deep impact on Diffusion Tensor Image (DTI) segmentation results. The geodesic metric is the best distance measure since it yields high-quality segmentation results. However, the important problem with the geodesic metric is a high computational cost of the algorithms based on it. The main goal of this ...

An Introduction to Sociolinguistics

An Introduction to Diffusion Maps

This paper describes a mathematical technique [1] for dealing with dimensionality reduction. Given data in a high-dimensional space, we show how to find parameters that describe the lower-dimensional structures of which it is comprised. Unlike other popular methods such as Principle Component Analysis and Multi-dimensional Scaling, diffusion maps are non-linear and focus on discovering the unde...