End-to-End Deep Learning Approach for Perfusion Data: A Proof-of-Concept Study to Classify Core Volume in Stroke CT

End-to-End Deep Learning Approach for Perfusion Data: A Proof-of-Concept Study to Classify Core Volume in Stroke CT

(1) Background: CT perfusion (CTP) is used to quantify cerebral hypoperfusion in acute ischemic stroke. Conventional attenuation curve analysis is not standardized and might require input from expert users, hampering clinical application. This study aims to bypass conventional tracer-kinetic analysi...

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Bibliographic Details
Main Authors: Andreas Mittermeier, Paul Reidler, Matthias P. Fabritius, Balthasar Schachtner, Philipp Wesp, Birgit Ertl-Wagner, Olaf Dietrich, Jens Ricke, Lars Kellert, Steffen Tiedt, Wolfgang G. Kunz, Michael Ingrisch
Format: Article
Language:English
Published: MDPI AG 2022-05-01
Series:Diagnostics
Subjects:
CT perfusion
stroke
deep learning
contrast-enhanced perfusion imaging
convolutional neural networks
end-to-end modeling
Online Access:https://www.mdpi.com/2075-4418/12/5/1142

Internet

https://www.mdpi.com/2075-4418/12/5/1142

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