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Lesion probability mapping in MS patients using a regression network on MR fingerprinting

To develop a regression neural network for the reconstruction of lesion probability maps on Magnetic Resonance Fingerprinting using echo-planar imaging (MRF-EPI) in addition to T1, T2∗, NAWM, and GM- probability maps.

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Bibliographic Details
Main Authors: Hermann, Ingo (Author) , Golla, Alena-Kathrin (Author) , Martínez-Heras, Eloy (Author) , Schmidt, Ralf (Author) , Solana, Elisabeth (Author) , Llufriu, Sara (Author) , Gass, Achim (Author) , Schad, Lothar R. (Author) , Zöllner, Frank G. (Author)
Format: Article (Journal)
Language:English
Published: 08 July 2021
In: BMC medical imaging
Year: 2021, Volume: 21, Pages: 1-11
ISSN:1471-2342
DOI:10.1186/s12880-021-00636-x
Online Access:Verlag, kostenfrei, Volltext: https://doi.org/10.1186/s12880-021-00636-x
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Author Notes:Ingo Hermann, Alena K. Golla, Eloy Martínez-Heras, Ralf Schmidt, Elisabeth Solana, Sara Llufriu, Achim Gass, Lothar R. Schad and Frank G. Zöllner
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Summary:To develop a regression neural network for the reconstruction of lesion probability maps on Magnetic Resonance Fingerprinting using echo-planar imaging (MRF-EPI) in addition to T1, T2∗, NAWM, and GM- probability maps.
Item Description:Gesehen am 05.07.2022
Physical Description:Online Resource
ISSN:1471-2342
DOI:10.1186/s12880-021-00636-x

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