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recurrent convolutional neural network  (Siemens Healthineers)

 
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    Siemens Healthineers recurrent convolutional neural network
    Recurrent Convolutional Neural Network, supplied by Siemens Healthineers, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/recurrent+convolutional+neural+network/recurrent+convolutional+neural+network/pm34841550-1-40-73
    Average 90 stars, based on 1 article reviews
    recurrent convolutional neural network - by Bioz Stars, 2026-11
    90/100 stars

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    Diffusion-based Assay:

    Article Title: Robust partial Fourier reconstruction for diffusion-weighted imaging using a recurrent convolutional neural network.
    Article Snippet: 2022;87:2018–2033.wileyonlinelibrary.com/journal/mrm Received: 24 May 2021 | Revised: 21 October 2021 | Accepted: 7 November 2021 DOI: 10.1002/mrm.29100 R E S E A R C H PA P E R Robust partial Fourier reconstruction for diffusion- weighted imaging using a recurrent convolutional neural network Fasil Gadjimuradov1,2 | Thomas Benkert2 | Marcel Dominik Nickel2 | Andreas Maier1 1Pattern Recognition Lab, Department of Computer Science, Friedrich- Alexander University Erlangen- Nürnberg, Erlangen, Germany 2Magnetic Resonance Applications Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany This is an open access article under the terms of the Creat ive Commo ns Attri bution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

    Imaging:

    Article Title: Robust partial Fourier reconstruction for diffusion-weighted imaging using a recurrent convolutional neural network.
    Article Snippet: 2022;87:2018–2033.wileyonlinelibrary.com/journal/mrm Received: 24 May 2021 | Revised: 21 October 2021 | Accepted: 7 November 2021 DOI: 10.1002/mrm.29100 R E S E A R C H PA P E R Robust partial Fourier reconstruction for diffusion- weighted imaging using a recurrent convolutional neural network Fasil Gadjimuradov1,2 | Thomas Benkert2 | Marcel Dominik Nickel2 | Andreas Maier1 1Pattern Recognition Lab, Department of Computer Science, Friedrich- Alexander University Erlangen- Nürnberg, Erlangen, Germany 2Magnetic Resonance Applications Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany This is an open access article under the terms of the Creat ive Commo ns Attri bution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.



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