English
 
User Manual Privacy Policy Disclaimer Contact us
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Poster

AWESOME-based de-noising of complex-valued fMRI time series

MPS-Authors
/persons/resource/persons98946

Marschner,  Henrik
Methods and Development Unit Nuclear Magnetic Resonance, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

/persons/resource/persons19914

Pampel,  André
Methods and Development Unit Nuclear Magnetic Resonance, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

/persons/resource/persons19864

Möller,  Harald E.
Methods and Development Unit Nuclear Magnetic Resonance, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

External Ressource
Fulltext (public)

Marschner-ISMRM2017_final_Monitor.pdf
(Publisher version), 2MB

Marschner-ISMRM2017_final.pdf
(Publisher version), 6MB

Supplementary Material (public)
There is no public supplementary material available
Citation

Marschner, H., Huber, L., Pampel, A., & Möller, H. E. (2017). AWESOME-based de-noising of complex-valued fMRI time series. Poster presented at ISMRM 25th Annual Meeting & Exhibition, Honolulu, HI, USA.


Cite as: http://hdl.handle.net/11858/00-001M-0000-002D-53EB-2
Abstract
In this study we investigate possible benefits of an application of ‘AWESOME’ de-noising on fMRI. The application in a high-SNR finger tapping experiment showed a reduction of the already low thermal noise contribution and therefore improvement of tSNR and reduction of false positives; no adverse effects in the form of smoothing or suppression of ‘true’ activation was observed. A second investigation of the scalability of tSNR improvement on a resting state experiment with variable slice thickness / SNR showed that thermal noise can be reliably reduced and the tSNR proportionally improved without visible reduction of detail sharpness / resolution.