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Least Squares Approaches to Diffusion Tensor Estimation 

Least Squares Approaches to Diffusion Tensor Estimation
Least Squares Approaches to Diffusion Tensor Estimation

Cheng Guan Koay

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date: 27 January 2020

Diffusion tensor imaging can be viewed as a data processing “pipeline” with various segments ranges from signal generation and detection to diffusion tensor estimation, and tractography. This chapter explores a particular segment of this pipeline, diffusion tensor estimation. The aim is to provide a straightforward introduction to a common class of estimation methods in diffusion tensor imaging with a special emphasis on the theoretical and algorithmic connections among the least squares methods through their respective objective functions and the higher order derivatives of these objective functions. It also considers the notion of a diffusion tensor representation to unify as well as simplify the presentation. This concept is a unifying idea in diffusion tensor imaging, especially in diffusion tensor estimation and error propagation or uncertainty assessment.

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