Diffusion Kurtosis Imaging with free water elimination: A Bayesian estimation approach

Purpose: Diffusion kurtosis imaging (DKI) is an advanced magnetic resonance imaging modality that is known to be sensitive to changes in the underlying microstructure of the brain. Image voxels in diffusion weighted images, however, are typically relatively large making them susceptible to partial volume effects, especially when part of the...

A nonlocal maximum likelihood estimation method for enhancing magnetic resonance phase maps

A phase map can be obtained from the real and imaginary components of a complex valued magnetic resonance (MR) image. Many applications, such as MR phase velocity mapping and susceptibility mapping, make use of the information contained in the MR phase maps. Unfortunately, noise in the complex MR signal affects the measurement of parameters...

Multi-voxel algorithm for quantitative bi-exponential MRI T₁ estimation

Quantification of the spin-lattice relaxation time, T₁, of tissues is important for characterization of tissues in clinical magnetic resonance imaging (MRI). In T₁ mapping, T₁ values are estimated from a set of T₁-weighted MRI images. Due to the limited spatial resolution of the T₁...

Robust estimation of the noise variance from background MR data

In the literature, many methods are available for estimation of the variance of the noise in magnetic resonance (MR) images. A commonly used method, based on the maximum of the background mode of the histogram, is revisited and a new, robust, and easy to use method is presented based on maximum likelihood (ML) estimation. Both methods are...