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  Deep learning-based post-processing of real-time MRI to assess and quantify dynamic wrist movement in health and disease

Radke, K. L., Wollschläger, L. M., Nebelung, S., Abrar, D. B., Schleich, C., Boschheidgen, M., et al. (2021). Deep learning-based post-processing of real-time MRI to assess and quantify dynamic wrist movement in health and disease. Diagnostics, 11, 1077. doi:10.3390/diagnostics11061077.

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3375043.pdf (Publisher version), 6MB
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 Creators:
Radke, K. L., Author
Wollschläger, L. M., Author
Nebelung, S., Author
Abrar, D. B., Author
Schleich, C., Author
Boschheidgen, M., Author
Frenken, M., Author
Schock, J., Author
Klee, D., Author
Frahm, J.1, Author           
Antoch, G., Author
Thelen, S., Author
Wittsack, H. J., Author
Müller-Lutz, A., Author
Affiliations:
1Research Group of Biomedical NMR, MPI for Biophysical Chemistry, Max Planck Society, ou_578633              

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Free keywords: magnetic resonance imaging; scapholunate ligament injury; carpal instability; real-time; deep learning; dynamic instability
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Language(s): eng - English
 Dates: 2021-06-062021-05-242021-06-092021-06-11
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.3390/diagnostics11061077
 Degree: -

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Title: Diagnostics
Source Genre: Journal
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Publ. Info: Basel : MPDI
Pages: 17 Volume / Issue: 11 Sequence Number: - Start / End Page: 1077 Identifier: ISSN: 2075-4418