RubiX: Combining Spatial Resolutions for Bayesian Inference of Crossing Fibres in Diffusion MRI

Keywords

according accuracy acquisition activity agree allows analyses another applied approaches assist assume assuming assumption audience ball benefits brain broader capsule category chain choice chosen coherent collecting combine combined combines combining concentration conditional conjunction constraints crossing crossings dataset datasets density details diffusion diffusivity distribution employed error estimation example fails field fraction fractions framework full funding furthermore fusion future generate generated generative governs graphical grid grids ground highest human hyper identifiability identified illustrate illustrates immediate imposed imposes improvements in vivo indirectly infer inference inferred instance introduce isotropic kingdom limitations local match matched mechanism miller model models noise noisier noisy noted novel object operates orientation orientations oxford partial patterns posterior predicted predictions principles prior priors project propagate proton rather reduces registered relate relates relatively resolution resolutions respectively revealed robustly scaled scanned section simple simpler simulated smith spatial specificity spending stick subset system target theorem tissue trade truth uncertainty underlying unified unify unknown valid variance volume white