Deep Learning for Magnetic Resonance Fingerprinting: Accelerating the Reconstruction of Quantitative Relaxation Maps

Hoppe E, Körzdorfer G, Nitka M, Würfl T, Wetzl J, Lugauer F, Schneider M, Pfeuffer J, Maier A (2018)

Publication Type: Conference contribution, Original article

Publication year: 2018

Pages Range: 2791

Conference Proceedings Title: Proceedings of the Joint Annual Meeting ISMRM-ESMRMB (26th Annual Meeting & Exhibition)

Event location: Paris, France

URI: https://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2018/Hoppe18-DLF.pdf

Authors with CRIS profile

Elisabeth Hoppe Lehrstuhl für Informatik 14 (Bild- und Sprachverarbeitung) Tobias Würfl Lehrstuhl für Informatik 5 (Mustererkennung) Jens Wetzl Lehrstuhl für Informatik 5 (Mustererkennung) Felix Lugauer Lehrstuhl für Informatik 14 (Bild- und Sprachverarbeitung) Manuel Schneider Lehrstuhl für Informatik 14 (Bild- und Sprachverarbeitung) Andreas Maier Lehrstuhl für Informatik 5 (Mustererkennung)

Involved external institutions

Siemens AG, Healthcare Sector

Germany (DE)

How to cite

APA:

Hoppe, E., Körzdorfer, G., Nitka, M., Würfl, T., Wetzl, J., Lugauer, F.,... Maier, A. (2018). Deep Learning for Magnetic Resonance Fingerprinting: Accelerating the Reconstruction of Quantitative Relaxation Maps. In Proceedings of the Joint Annual Meeting ISMRM-ESMRMB (26th Annual Meeting & Exhibition) (pp. 2791). Paris, France.

MLA:

Hoppe, Elisabeth, et al. "Deep Learning for Magnetic Resonance Fingerprinting: Accelerating the Reconstruction of Quantitative Relaxation Maps." Proceedings of the Proceedings of the Joint Annual Meeting ISMRM-ESMRMB (26th Annual Meeting & Exhibition), Paris, France 2018. 2791.

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