no code implementations • 25 Jan 2022 • Gerard Snaauw, Michele Sasdelli, Gabriel Maicas, Stephan Lau, Johan Verjans, Mark Jenkinson, Gustavo Carneiro
We propose guiding the training of a deep learning-based registration method with MI estimation between an image-pair in an end-to-end trainable network.
no code implementations • 23 Oct 2018 • Gerard Snaauw, Dong Gong, Gabriel Maicas, Anton Van Den Hengel, Wiro J. Niessen, Johan Verjans, Gustavo Carneiro
In this paper, we propose a learning method to train diagnosis models, where our approach is designed to work with relatively small datasets.
no code implementations • 20 Jul 2018 • Gabriel Maicas, Gerard Snaauw, Andrew P. Bradley, Ian Reid, Gustavo Carneiro
There is a heated debate on how to interpret the decisions provided by deep learning models (DLM), where the main approaches rely on the visualization of salient regions to interpret the DLM classification process.