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Found 5 papers, 2 papers with code
Knowing what you know in brain segmentation using Bayesian deep neural networks
In this paper, we describe a Bayesian deep neural network (DNN) for predicting FreeSurfer segmentations of structural MRI volumes, in minutes rather than hours.
Extrapolating Expected Accuracies for Large Multi-Class Problems
The difficulty of multi-class classification generally increases with the number of classes.
Learning Summary Statistic for Approximate Bayesian Computation via Deep Neural Network
Approximate Bayesian Computation (ABC) methods are used to approximate posterior distributions in models with unknown or computationally intractable likelihoods.
Quantifying error in estimates of human brain fiber directions using Earth Mover's Distance
To elucidate the structure of these connections, algorithms for tracking bundles of axonal fibers through the subcortical white matter rely on local estimates of the fiber orientation distribution function (fODF) in different parts of the brain.
Deconvolution of High-Dimensional Mixtures via Boosting, with Application to Diffusion-Weighted MRI of Human Brain
Diffusion-weighted magnetic resonance imaging (DWI) and fiber tractography are the only methods to measure the structure of the white matter in the living human brain.
