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  STI and DTI: Tensor Characteristics and a machine-learning approach to estimate susceptibility tensors

Gkotsoulias, D., Metere, R., Eichner, C., Schlumm, T., Anwander, A., Jäger, C., et al. (2020). STI and DTI: Tensor Characteristics and a machine-learning approach to estimate susceptibility tensors. Poster presented at Fachbeirat 2020, Virtual.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0007-1F07-0 Version Permalink: http://hdl.handle.net/21.11116/0000-0007-1F08-F
Genre: Poster

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poster_NMR1_gkotsoulias.pdf (Abstract), 2MB
Name:
Fachbeirat 2020, Gkotsoulias Dimitrios, NMR Group, Poster
Description:
Comparisons between STI and DTI Tensor Characteristics derived using high angular post-mortem Chimpanzee brain datasets and a Machine-Learning Approach to Estimate Susceptibility Tensors.
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application/pdf / [MD5]
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 Creators:
Gkotsoulias, Dimitrios1, Author              
Metere, Riccardo, Author              
Eichner, Cornelius2, Author              
Schlumm, Torsten1, Author              
Anwander, Alfred2, Author              
Jäger, Carsten3, Author              
Pampel, André1, Author              
Crockford, Catherine, Author
Roman, Wittig, Author
Liu, Chunlei, Author
Su, Yanzhu, Author
Möller, Harald E.1, Author              
Affiliations:
1Methods and Development Unit Nuclear Magnetic Resonance, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634558              
2Department Neuropsychology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634551              
3Department Neurophysics (Weiskopf), MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_2205649              

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Free keywords: Suscptibility, Diffusion, STI, DTI
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Language(s): eng - English
 Dates: 2020-02-17
 Publication Status: Not specified
 Pages: 1
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Title: Fachbeirat 2020
Place of Event: Virtual
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