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Ultra-High-Resolution Imaging of the Human Brain at 9.4 T Using k-Space Weighted Acquisition

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Budde,  J
Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Shajan,  G
Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Scheffler,  K
Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Pohmann,  R
Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Citation

Budde, J., Shajan, G., Scheffler, K., & Pohmann, R. (2013). Ultra-High-Resolution Imaging of the Human Brain at 9.4 T Using k-Space Weighted Acquisition. Poster presented at 21st Annual Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine (ISMRM 2013), Salt Lake City, UT, USA.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0013-B498-3
Abstract
Imaging with high spatial resolutions suffers from low SNR, long durations and high sensitivity to artifacts. K-space weighted imaging by acquiring a varying number of averages depending on the position in k-space constitutes a means to reduce signal contamination from adjacent voxels as well as to increase the apparent SNR. The resulting advantages are evaluated for high resolution human brain imaging at 9.4 T, yielding a gain in SNR of between 15 % and 28 % compared to conventional 3D GRE. With this technique, it was possible to acquire images from the human brain with voxel volumes of 14 nl.