102 citations · 128 across the 4 of their papers we have counts for
4 papers
Automated Labelling using an Attention model for Radiology reports of MRI scans (ALARM)
David A. Wood, Jeremy Lynch, Sina Kafiabadi +13
Labelling large datasets for training high-capacity neural networks is a major obstacle to the development of deep learning-based medical imaging applications. Here we present a tr…
NEURO-DRAM: a 3D recurrent visual attention model for interpretable neuroimaging classification
David Wood, James Cole, Thomas Booth
Deep learning is attracting significant interest in the neuroimaging community as a means to diagnose psychiatric and neurological disorders from structural magnetic resonance imag…
An Update on Machine Learning in Neuro-oncology Diagnostics
Thomas Booth
Imaging biomarkers in neuro-oncology are used for diagnosis, prognosis and treatment response monitoring. Magnetic resonance imaging is typically used throughout the patient pathwa…
Machine learning and glioma imaging biomarkers
Thomas Booth, Matthew Williams, Aysha Luis +3
Aim: To review how machine learning (ML) is applied to imaging biomarkers in neuro-oncology, in particular for diagnosis, prognosis, and treatment response monitoring. Materials an…