3.7k citations · 4.1k across the 26 of their papers we have counts for
4 papers · 1 filter
Bayesian Non-Central Chi Regression For Neuroimaging
Bertil Wegmann, Anders Eklund, Mattias Villani
We propose a regression model for non-central (NC-) distributed functional magnetic resonance imaging (fMRI) and diffusion weighted imaging (DWI) data, with the heteroscedas…
A Bayesian Heteroscedastic GLM with Application to fMRI Data with Motion Spikes
Anders Eklund, Martin A. Lindquist, Mattias Villani
We propose a voxel-wise general linear model with autoregressive noise and heteroscedastic noise innovations (GLMH) for analyzing functional magnetic resonance imaging (fMRI) data.…
Gaussian process regression can turn non-uniform and undersampled diffusion MRI data into diffusion spectrum imaging
Jens Sjölund, Anders Eklund, Evren Özarslan +1
We propose to use Gaussian process regression to accurately estimate the diffusion MRI signal at arbitrary locations in q-space. By estimating the signal on a grid, we can do synth…
Fast Bayesian whole-brain fMRI analysis with spatial 3D priors
Per Sidén, Anders Eklund, David Bolin +1
Spatial whole-brain Bayesian modeling of task-related functional magnetic resonance imaging (fMRI) is a great computational challenge. Most of the currently proposed methods theref…