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Neurosense: deep sensing of full or near-full coverage head/brain scans in human magnetic resonance imaging

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Notes

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Acknowledgements

We are grateful to Professor Frederik Barkhof, Professor Daniel Alexander, Dr. Parashkev Nachev, Dr. Robert Gray, Dr. Ferran Prados, and Dr. Eugenio Iglesias for their help and support of this study, and for providing comments on a previous versions of the article. The data used were provided in part by OASIS and were part based upon data generated by the TCGA Research Network. This work was funded by the National Institute for Health Research University College London Hospitals Biomedical Research Centre, and the Wellcome Trust.

Author information

Authors and Affiliations

  1. UCL Centre for Medical Image Computing, University College London, 90 High Holborn, Holborn, London, WC1V 6LJ, UK

    Baris Kanber

  2. Department of Medical Physics and Biomedical Engineering, University College London, London, UK

    Baris Kanber

  3. National Institute for Health Research University College London Hospitals Biomedical Research Centre, London, UK

    Baris Kanber & Olga Ciccarelli

  4. Department of Radiology, University College London Hospitals NHS Foundation Trust, London, UK

    James Ruffle

  5. School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK

    Jorge Cardoso & Sebastien Ourselin

  6. Department of Neuroinflammation, Queen Square Institute of Neurology, University College London, London, UK

    Olga Ciccarelli

Authors
  1. Baris Kanber
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  2. James Ruffle
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  3. Jorge Cardoso
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  4. Sebastien Ourselin
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  5. Olga Ciccarelli
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Corresponding author

Correspondence to Baris Kanber.

Ethics declarations

This study was approved by the University College London Hospitals NHS Trust. The study was classified as a service evaluation and optimization project using irrevocably anonymized data, which does not require ethical approval or consent.

Information Sharing Statement

Neurosense is available for use as a virtual machine from CMIClab. The datasets used during development are publicly available except for the UCLH dataset which is not a public database.

Conflict of Interest

The authors declare that they have no conflicts of interest.

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Kanber, B., Ruffle, J., Cardoso, J. et al. Neurosense: deep sensing of full or near-full coverage head/brain scans in human magnetic resonance imaging. Neuroinform 18, 333–336 (2020). https://doi.org/10.1007/s12021-019-09442-x

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