Hardware Failure Prediction on Imbalanced Times Series Data: Generation of Artificial Data Using Gaussian Process and Applying LSTMFCN to Predict Broken Hardware

Magnetic resonance imaging (MRI) systems and their continuous, failure-free operation is crucial for high-quality diagnostics and seamless workflows. One important hardware component is coils as they detect the magnetic signal. Before every MRI scan, several image features are captured which represe...

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Detalles Bibliográficos
Autores principales: Rücker, Nadine, Pflüger, Lea, Maier, Andreas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2021
Materias:
Original Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7887121/
https://www.ncbi.nlm.nih.gov/pubmed/33409816
http://dx.doi.org/10.1007/s10278-020-00411-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7887121/
https://www.ncbi.nlm.nih.gov/pubmed/33409816
http://dx.doi.org/10.1007/s10278-020-00411-4

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