AI-driven and automated MRI sequence optimization in scanner-independent MRI sequences formulated by a domain-specific language

AI-driven and automated MRI sequence optimization in scanner-independent MRI sequences formulated by a domain-specific language

IntroductionThe complexity of Magnetic Resonance Imaging (MRI) sequences requires expert knowledge about the underlying contrast mechanisms to select from the wide range of available applications and protocols. Automation of this process using machine learning (ML) can support the radiologists and M...

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Bibliographic Details
Main Authors: Daniel Christopher Hoinkiss, Jörn Huber, Christina Plump, Christoph Lüth, Rolf Drechsler, Matthias Günther
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-05-01
Series:Frontiers in Neuroimaging
Subjects:
domain specific language
magnetic resonance imaging
machine learning
simulation
optimization
automation
Online Access:https://www.frontiersin.org/articles/10.3389/fnimg.2023.1090054/full

Internet

https://www.frontiersin.org/articles/10.3389/fnimg.2023.1090054/full

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