3D Cardiac Shape Prediction with Deep Neural Networks: Simultaneous Use of Images and Patient Metadata

no code implementations • 2 Jul 2019 • Rahman Attar, Marco Pereanez, Christopher Bowles, Stefan K. Piechnik, Stefan Neubauer, Steffen E. Petersen, Alejandro F. Frangi

We validated our proposed CMR analytics method against a reference cohort containing 500 3D shapes of the cardiac ventricles.

GANsfer Learning: Combining labelled and unlabelled data for GAN based data augmentation

no code implementations • 26 Nov 2018 • Christopher Bowles, Roger Gunn, Alexander Hammers, Daniel Rueckert

We also show how a shift in domain of the training data from young and healthy towards older and more pathological examples leads to better segmentations of the latter cases, and that this leads to a significant improvement in the ability for the computed segmentations to stratify cases of AD.

Data Augmentation Segmentation

GAN Augmentation: Augmenting Training Data using Generative Adversarial Networks

no code implementations • 25 Oct 2018 • Christopher Bowles, Liang Chen, Ricardo Guerrero, Paul Bentley, Roger Gunn, Alexander Hammers, David Alexander Dickie, Maria Valdés Hernández, Joanna Wardlaw, Daniel Rueckert

One of the biggest issues facing the use of machine learning in medical imaging is the lack of availability of large, labelled datasets.

BIG-bench Machine Learning Brain Segmentation