Segmentation method for cerebral blood vessels from MRA using hysteresis

no code implementations • 9 Mar 2023 • Georgia Kenyon, Stephan Lau, Michael A. Chappell, Mark Jenkinson

Due to the absence of open-source tools, we aim to develop a classical segmentation method that generates vessel ground truth from Magnetic Resonance Angiography for DL training of segmentation across a variety of modalities.

Segmentation

Stochastic Variational Bayesian Inference for a Nonlinear Forward Model

no code implementations • 3 Jul 2020 • Michael A. Chappell, Martin S. Craig, Mark W. Woolrich

Variational Bayes (VB) has been used to facilitate the calculation of the posterior distribution in the context of Bayesian inference of the parameters of nonlinear models from data.

Bayesian Inference

The FMRIB Variational Bayesian Inference Tutorial II: Stochastic Variational Bayes

no code implementations • 3 Jul 2020 • Michael A. Chappell, Mark W. Woolrich

Hence methods for Bayesian inference have historically either been significantly approximate, e. g., the Laplace approximation, or achieve samples from the exact solution at significant computational expense, e. g., Markov Chain Monte Carlo methods.

Bayesian Inference BIG-bench Machine Learning