Optimized bias and signal inference in diffusion-weighted image analysis (OBSIDIAN).

ABSTRACT:

Purpose

Correction of Rician signal bias in magnitude MR images.

Methods

A model-based, iterative fitting procedure is used to simultaneously estimate true signal and underlying Gaussian noise with standard deviation σg on a pixel-by-pixel basis in magnitude MR images. A precomputed function that relates absolute residuals between measured signals and model fit to σg is used to iteratively estimate σg . The feasibility of the method is evaluated and compared to maximum likelihood estimation (MLE) for diffusion signal decay simulations and diffusion-weighted images of the prostate considering 21 linearly spaced b-values from 0 to 3000 s/mm² . A multidirectional analysis was performed with publically available brain data.

Results

Model simulations show that t

SUBMITTER: Kuczera S 

PROVIDER: S-EPMC9009782 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature