Healthy Kidney Segmentation in the Dce-Mr Images Using a Convolutional Neural Network and Temporal Signal Characteristics

Healthy Kidney Segmentation in the Dce-Mr Images Using a Convolutional Neural Network and Temporal Signal Characteristics

Quantification of renal perfusion based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) requires determination of signal intensity time courses in the region of renal parenchyma. Thus, selection of voxels representing the kidney must be accomplished with special care and constitute...

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Bibliographic Details
Main Authors: Artur Klepaczko, Eli Eikefjord, Arvid Lundervold
Format: Article
Language:English
Published: MDPI AG 2021-10-01
Series:Sensors
Subjects:
dynamic contrast-enhanced MRI
convolutional neural networks
kidney segmentation
pharmocokinetic modeling
perfusion quantification
glomerular filtration rate
Online Access:https://www.mdpi.com/1424-8220/21/20/6714

Internet

https://www.mdpi.com/1424-8220/21/20/6714

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