1 citations · 1 across the 4 of their papers we have counts for
4 papers
Segmentation method for cerebral blood vessels from MRA using hysteresis
Georgia Kenyon, Stephan Lau, Michael A. Chappell +1
Segmentation of cerebral blood vessels from Magnetic Resonance Imaging (MRI) is an open problem that could be solved with deep learning (DL). However, annotated data for training i…
Time-encoded pseudo-continuous arterial spin labeling: increasing SNR in ASL angiography
Joseph G. Woods, S. Sophie Schauman, Mark Chiew +2
Purpose: Dynamic angiography using arterial spin labeling (ASL) can provide detailed hemodynamic information. However, the long time-resolved readouts require small flip angles to…
The FMRIB Variational Bayesian Inference Tutorial II: Stochastic Variational Bayes
Michael A. Chappell, Mark W. Woolrich
Bayesian methods have proved powerful in many applications for the inference of model parameters from data. These methods are based on Bayes' theorem, which itself is deceptively s…
Stochastic Variational Bayesian Inference for a Nonlinear Forward Model
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 dat…