21 citations · 26 across the 5 of their papers we have counts for
5 papers
AA-ViT: Anatomically Aware Vision Transformer with Structural and Frequency Guidance for Contrast Enhanced Brain MRI Synthesis
Talha Meraj, Tom Flannery, Charlie Cummins +6
Accurate tumour localization and diagnosis is a critical component of clinical care for brain cancers. Magnetic Resonance Imaging (MRI) is the most commonly used imaging modality d…
A self-supervised text-vision framework for automated brain abnormality detection
David A. Wood, Emily Guilhem, Sina Kafiabadi +13
Artificial neural networks trained on large, expert-labelled datasets are considered state-of-the-art for a range of medical image recognition tasks. However, categorically labelle…
Automated triaging of head MRI examinations using convolutional neural networks
David A. Wood, Sina Kafiabadi, Ayisha Al Busaidi +9
The growing demand for head magnetic resonance imaging (MRI) examinations, along with a global shortage of radiologists, has led to an increase in the time taken to report head MRI…
Labelling imaging datasets on the basis of neuroradiology reports: a validation study
David A. Wood, Sina Kafiabadi, Aisha Al Busaidi +11
Natural language processing (NLP) shows promise as a means to automate the labelling of hospital-scale neuroradiology magnetic resonance imaging (MRI) datasets for computer vision…
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…