Now showing items 1-4 of 4

    • Augmenting dementia cognitive assessment with instruction-less eye-tracking tests 

      Mengoudi, Kyriaki; Ravi, Daniele; Yong, Keir X.X.; Primativo, Silvia; Pavisic, Ivanna M.; Brotherhood, Emilie; Lu, Kirsty; Schott, Jonathan M.; Crutch, Sebastian J.; Alexander, Daniel C. (2020-11)
      Eye-tracking technology is an innovative tool that holds promise for enhancing dementia screening. In this work, we introduce a novel way of extracting salient features directly from the raw eye-tracking data of a mixed ...
    • DeepBrainPrint: A Novel Contrastive Framework for Brain MRI Re-Identification 

      Puglisi, Lemuel; Barkhof, Frederik; Alexander, Daniel C.; Parker, Geoffrey JM; Eshaghi, Arman; Ravi, Daniele (2023-07-12)
      Recent advances in MRI have led to the creation of large datasets. With the increase in data volume, it has become difficult to locate previous scans of the same patient within these datasets (a process known as ...
    • Degenerative adversarial neuroimage nets for brain scan simulations: Application in ageing and dementia 

      for the Alzheimer's Disease Neuroimaging Initiative; Ravi, Daniele; Blumberg, Stefano B.; Ingala, Silvia; Barkhof, Frederik; Alexander, Daniel C.; Oxtoby, Neil P. (2022-01-01)
      Accurate and realistic simulation of high-dimensional medical images has become an important research area relevant to many AI-enabled healthcare applications. However, current state-of-the-art approaches lack the ability ...
    • An efficient semi-supervised quality control system trained using physics-based MRI-artefact generators and adversarial training 

      Alzheimer’s Disease Neuroimaging Initiative; Ravi, Daniele; Barkhof, Frederik; Alexander, Daniel C.; Puglisi, Lemuel; Parker, Geoffrey J.M.; Eshaghi, Arman (2024-01-30)
      Large medical imaging data sets are becoming increasingly available. A common challenge in these data sets is to ensure that each sample meets minimum quality requirements devoid of significant artefacts. Despite a wide ...