A machine-learning framework for automatic reference-free quality assessment in MRI

Magnetic resonance (MR) imaging offers a wide variety of imaging techniques. A large amount of data is created per examination which needs to be checked for sufficient quality in order to derive a meaningful diagnosis. This is a manual process and therefore time- and cost-intensive. Any imaging arti...

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Veröffentlicht in:	Magnetic resonance imaging 2018-11, Vol.53, p.134-147
Hauptverfasser:	Küstner, T., Gatidis, S., Liebgott, A., Schwartz, M., Mauch, L., Martirosian, P., Schmidt, H., Schwenzer, NF, Nikolaou, K., Bamberg, F., Yang, B., Schick, F.
Format:	Artikel
Sprache:	eng
Schlagworte:	Deep learning Image quality assessment Machine-learning Magnetic resonance imaging Non-reference/blind
Online-Zugang:	Volltext
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