Applying machine learning classifiers to automate quality assessment of paediatric dynamic susceptibility contrast (DSC-) MRI data
- Stephen J Powell
- , Stephanie B Withey
- , Yu Sun
- , James T Grist
- , Jan Novak
- , Lesley MacPherson
- , Laurence Abernethy
- , Barry Pizer
- , Richard Grundy
- , Paul S Morgan
- , Tim Jaspan
- , Simon Bailey
- , Dipayan Mitra
- , Dorothee P Auer
- , Shivaram Avula
- , Theodoros N Arvanitis
- , Andrew Peet
- D Larner, Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, United Kingdom of Great Britain and Northern Ireland.
- RRPPS, University Hospitals Birmingham NHS Foundation Trust, Birmingham, United Kingdom.
- School of Biological Sciences and Medical Engineering, Southeast University, Nanjing, China.
- Radiology, Birmingham Children's Hospital, Birmingham, United Kingdom.
- Radiology, Alder Hey Children's NHS Foundation Trust, Liverpool, United Kingdom.
- Oncology, Alder Hey Children's NHS Foundation Trust, Liverpool, United Kingdom.
- The Children's Brain Tumour Research Centre, University of Nottingham, Nottingham, United Kingdom.
- NIHR Nottingham Biomedical Research Centre, Nottingham, United Kingdom.
- Radiology, Nottingham University Hospitals, Nottingham, United Kingdom.
- Sir James Spence Institute of Child Health, Royal Victoria Infirmary, Newcastle upon Tyne, United Kingdom.
- Neuroradiology, The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, United Kingdom.
- Sir Peter Mansfield Imaging Centre, University of Nottingham Biomedical Research Centre, Nottingham, United Kingdom
- University Hospitals Coventry & Warwickshire NHS Trust, Clifford Bridge Road, Coventry, CV2 2DX, United Kingdom; Institute of Digital Healthcare, WMG, University of Warwick, Coventry, CV4 7AL, United Kingdom
- Department of Oncology, Birmingham Children's Hospital, Birmingham, United Kingdom.
Research output: Contribution to journal › Article › peer-review
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