Susan Francis 1,2, Charlotte E Buchanan1, Martin Craig1,2, Alexander J Daniel1, Andrew N Priest3, Eleanor F Cox1,2, Margot Roeth1,2, James P Stowe1, Kevin Teh4, David L Thomas5,6,7, Mark Gilthorpe8, Philip Kalra9, Maarten Taal10, Iosif A Mendichovszky11, Steven Sourbron4, Nicholas Selby10
1Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, United Kingdom
2Nottingham Biomedical Research Centre, National Institute for Health Research, Nottingham, United Kingdom
3Department of Radiology, University of Cambridge, Cambridge, United Kingdom
4Department of Infection, Immunity and Cardiovascular Disease, The University of Sheffield, Sheffield, United Kingdom
5Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
6Department of Translational Neuroscience and Stroke, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
7Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
8Obesity Institute, Leeds Beckett University, Leeds, United Kingdom
9Salford Royal NHS Foundataion Trust, Salford, United Kingdom
10Centre for Kidney Research and Innovation, University of Nottingham, Nottingham, United Kingdom
11Department of Radiology, Addenbrooke's Hospital, Cambridge, United Kingdom
Presenting Author: Susan Francis
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1. Kidney Disease: UK public health emergency. The health economics of kidney disease to 2033 Kidney Research UK.
2. Application of Functional Renal MRI to improve assessment of chronic kidney disease (AFiRM) study website: https://www.uhdb.nhs.uk/afirm-study/
3. UKRIN-MAPS (MRI Acquisition and Processing Standardisation) website: https://www.nottingham.ac.uk/research/groups/spmic/research/uk-renal-imaging-network/ukrin-maps.aspx
4. Daniel AJ, Buchanan CE, Allcock T, Scerri D, Cox EF, Prestwich BL, Francis ST. Automated renal segmentation in healthy and chronic kidney disease subjects using a convolutional neural network, Magn. Reson. Med., 86, Issue2, 1125-113, 2021.
5. Cox EC, Gong Z, Craig M, Mohammadi-Nejad A-R, Auer D, Sotiropoulos S, Chen X, Francis S. Automated Analysis of Kidney MRI data in the UK Biobank. 5th Renal MRI meeting, Ghent, 2023.
6. Li H, Buchanan CE, Morris DM, Daniel AJ, Sousa J, Sourbron S, Thomas DL, Francis ST, Priest AN. Improved Harmonization of Renal T2 Mapping Between Vendors using Stimulated Echo Compensation. In: Proc. Intl. Soc. Mag. Reson. Med. 2022, 4409