Analysis of the effects of noise, DWI sampling, and value of assumed parameters in diffusion MRI models.

ABSTRACT:

Purpose

This study was a systematic evaluation across different and prominent diffusion MRI models to better understand the ways in which scalar metrics are influenced by experimental factors, including experimental design (diffusion-weighted imaging [DWI] sampling) and noise.

Methods

Four diffusion MRI models-diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), mean apparent propagator MRI (MAP-MRI), and neurite orientation dispersion and density imaging (NODDI)-were evaluated by comparing maps and histogram values of the scalar metrics generated using DWI datasets obtained in fixed mouse brain with different noise levels and DWI sampling complexity. Additionally, models were fit with different input parameters or constraints to examine the consequences of mode

SUBMITTER: Hutchinson EB 

PROVIDER: S-EPMC6084345 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature