no code implementations • 29 Sep 2023 • Alessandro Fontanella, Wenwen Li, Grant Mair, Antreas Antoniou, Eleanor Platt, Paul Armitage, Emanuele Trucco, Joanna Wardlaw, Amos Storkey
DL methods can be designed for AIS lesion detection on CT using the vast quantities of routinely-collected CT brain scan data.
no code implementations • 26 Sep 2023 • Alessandro Fontanella, Wenwen Li, Grant Mair, Antreas Antoniou, Eleanor Platt, Chloe Martin, Paul Armitage, Emanuele Trucco, Joanna Wardlaw, Amos Storkey
Despite the large amount of brain CT data generated in clinical practice, the availability of CT datasets for deep learning (DL) research is currently limited.
1 code implementation • 3 Aug 2023 • Alessandro Fontanella, Grant Mair, Joanna Wardlaw, Emanuele Trucco, Amos Storkey
Segmentation masks of pathological areas are useful in many medical applications, such as brain tumour and stroke management.
1 code implementation • 27 Mar 2023 • Alessandro Fontanella, Antreas Antoniou, Wenwen Li, Joanna Wardlaw, Grant Mair, Emanuele Trucco, Amos Storkey
We investigate the best way to generate the saliency maps employed in our architecture and propose a way to obtain them from adversarially generated counterfactual images.
no code implementations • 5 Apr 2018 • Enrico Pellegrini, Lucia Ballerini, Maria del C. Valdes Hernandez, Francesca M. Chappell, Victor González-Castro, Devasuda Anblagan, Samuel Danso, Susana Muñoz Maniega, Dominic Job, Cyril Pernet, Grant Mair, Tom MacGillivray, Emanuele Trucco, Joanna Wardlaw
METHODS: We systematically reviewed the literature, 2006 to late 2016, for machine learning studies differentiating healthy ageing through to dementia of various types, assessing study quality, and comparing accuracy at different disease boundaries.