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Abstract #1462

AWESOME-Based De-Noising of Complex-Valued fMRI Time Series

Henrik Marschner1, Laurentius Huber2, André Pampel1, and Harald E. Möller1

1NMR, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, 2Section on Functional Imaging Methods, National Institute of Mental Health, Bethesda, MD, United States

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.

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