Overcoming challenges of translating deep-learning models for glioblastoma: the ZGBM consortium

no code implementations • 7 May 2024 • Haris Shuaib, Gareth J Barker, Peter Sasieni, Enrico De Vita, Alysha Chelliah, Roman Andrei, Keyoumars Ashkan, Erica Beaumont, Lucy Brazil, Chris Rowland-Hill, Yue Hui Lau, Aysha Luis, James Powell, Angela Swampillai, Sean Tenant, Stefanie C Thust, Stephen Wastling, Tom Young, Thomas C Booth

Diffusion MRI is the most common non-structural imaging type, performed at every site.

Scheduling

A self-supervised text-vision framework for automated brain abnormality detection

no code implementations • 5 May 2024 • David A. Wood, Emily Guilhem, Sina Kafiabadi, Ayisha Al Busaidi, Kishan Dissanayake, Ahmed Hammam, Nina Mansoor, Matthew Townend, Siddharth Agarwal, Yiran Wei, Asif Mazumder, Gareth J. Barker, Peter Sasieni, Sebastien Ourselin, James H. Cole, Thomas C. Booth

To address these challenges, we present a self-supervised text-vision framework that learns to detect clinically relevant abnormalities in brain MRI scans by directly leveraging the rich information contained in accompanying free-text neuroradiology reports.

Anomaly Detection Language Modelling +1