Non-Local Means Denoising of 7T Functional MR Images: Enhancing Spatial Accuracy of Fine-Grained Task-Specific Neurosignatures?
Igor Fabian Tellez Ceja1, Thomas Gladytz1, Ludger Benedikt Starke1, Karsten Tabelow2, Thoralf Niendorf1,3, and Henning Matthias Reimann1
1Berlin Ultrahigh Field Facility (B.U.F.F.), Max Delbrück Center for Molecular Medicine, Berlin, Germany, 2Weierstrass Institute for Applied Analysis and Stochastics, Berlin, Germany, 3Experimental and Clinical Research Center (ECRC), a joint cooperation between the Charité Medical Faculty and the Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
Superior spatial fidelity of fMRI at ultrahigh magnetic field strengths (≥7T) in principle allows for resolving fine grained task-specific fMRI neurosignatures. Yet, spatial details of BOLD clusters are conventionally blurred by Gaussian smoothing. To preserve spatial details, spatial-adaptive non-local means (SANLM) denoising has been introduced in fMRI as an alternative to Gaussian smoothing. Here, we evaluate SANLM denoising at 7T. SANLM removes noise in homogeneous areas while maintaining edges. It prevents the spread of BOLD patterns between adjacent brain regions, but should be employed with caution, as its spatial detail is partially driven by the underlying anatomy.
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