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.
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.
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.