English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
 
 
DownloadE-Mail
  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.

Item is

Files

show Files
hide Files
:
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.
OA-Status:
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
Copyright Date:
-
Copyright Info:
-
License:
-

Locators

show

Creators

show
hide
 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              

Content

show
hide
Free keywords: Suscptibility, Diffusion, STI, DTI
 Abstract: -

Details

show
hide
Language(s): eng - English
 Dates: 2020-02-17
 Publication Status: Not specified
 Pages: 1
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: -
 Degree: -

Event

show
hide
Title: Fachbeirat 2020
Place of Event: Virtual
Start-/End Date: -

Legal Case

show

Project information

show

Source

show