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Poster

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

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

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

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

Externe Ressourcen

http://indexsmart.mirasmart.com/ISMRM2017/PDFfiles/1462.html
(Ergänzendes Material)

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Volltexte (frei zugänglich)

Marschner-ISMRM2017_final.pdf
(Verlagsversion), 6MB

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Zitation

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.


Zitierlink: https://hdl.handle.net/11858/00-001M-0000-002D-53EB-2
Zusammenfassung
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.