Feasibility and benefits of joint learning from MRI databases with different brain diseases and modalities for segmentation

no code implementations • 28 May 2024 • Wentian Xu, Matthew Moffat, Thalia Seale, Ziyun Liang, Felix Wagner, Daniel Whitehouse, David Menon, Virginia Newcombe, Natalie Voets, Abhirup Banerjee, Konstantinos Kamnitsas

Results demonstrate, for the first time, that joint training on multi-modal MRI databases with different brain pathologies and sets of modalities is feasible and offers practical benefits.

Transductive image segmentation: Self-training and effect of uncertainty estimation

no code implementations • 19 Jul 2021 • Konstantinos Kamnitsas, Stefan Winzeck, Evgenios N. Kornaropoulos, Daniel Whitehouse, Cameron Englman, Poe Phyu, Norman Pao, David K. Menon, Daniel Rueckert, Tilak Das, Virginia F. J. Newcombe, Ben Glocker

It focuses on the quality of predictions made on the unlabeled data of interest when they are included for optimization during training, rather than improving generalization.

Image Segmentation Medical Image Segmentation +3

A Survey of Monte Carlo Tree Search Methods

1 code implementation • IEEE Transactions on Computational Intelligence and AI in Games 2012 • Cameron B. Browne, Edward Powley, Daniel Whitehouse, Simon M. Lucas, Peter I. Cowling, Philipp Rohlfshagen, Stephen Tavener, Diego Perez, Spyridon Samothrakis, Simon Colton

Monte Carlo Tree Search (MCTS) is a recently proposed search method that combines the precision of tree search with the generality of random sampling.