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Abstract #5442

Effect of optimised coil-combinations on high-resolution laminar fMRI at 9.4T

Sriranga Kashyap1,2, Francisco J. Fritz1,2, Robbert L. Harms1, Laurentius Huber3, Dimo Ivanov1,2, Alard Roebroeck1,2, Benedikt A. Poser1,2, and Kâmil Uludağ1,2

1Department of Cognitive Neuroscience, Maastricht University, Maastricht, Netherlands, 2Maastricht Brain Imaging Centre (MBIC), Maastricht, Netherlands, 3Section on Functional Imaging Methods Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, MD, United States

Despite the availability of more sophisticated coil-combination methods like Roemer and STARC, ultra-high field fMRI studies still use the conventional sum-of-squares (SoS) method for combining the images of the individual coils from multi-channel RF-coil arrays. Here we use a memory-efficient, CPU/GPU accelerated coil-combine toolbox written in Python to compare and characterise the effect of methods such as covariance-weighted sum-of-squares (CovSoS), Roemer and STARC on sub-millimetre resolution GE-EPI laminar fMRI data acquired at 9.4T, and demonstrate the benefit of using optimised coil-combination for UHF fMRI studies.

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