Automated renal segmentation in healthy and chronic kidney disease subjects using a convolutional neural network.

Journal: Magnetic resonance in medicine

Published Date: Mar 23, 2021

Abstract

PURPOSE: Total kidney volume (TKV) is an important measure in renal disease detection and monitoring. We developed a fully automated method to segment the kidneys from T -weighted MRI to calculate TKV of healthy control (HC) and chronic kidney disease (CKD) patients.

Authors

Alexander J Daniel

Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, United Kingdom.
Charlotte E Buchanan

Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, United Kingdom.
Thomas Allcock

Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, United Kingdom.
Daniel Scerri

Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, United Kingdom.
Eleanor F Cox

Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, United Kingdom.
Benjamin L Prestwich

Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, United Kingdom.
Susan T Francis

Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, United Kingdom.

Keywords

Humans Image Processing, Computer-Assisted Kidney Machine Learning Magnetic Resonance Imaging Neural Networks, Computer Renal Insufficiency, Chronic

External Resources

View on PubMed Access via DOI PubMed (33755256)

Automated renal segmentation in healthy and chronic kidney disease subjects using a convolutional neural network.

Abstract

Authors

Keywords

External Resources

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