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Abstract #3667

Optimizing a preprocessing pipeline for structural 7T MR analyses in FreeSurfer

Giske Opheim1,2, Oula Puonti3,4, Jan Ole Pedersen5, Vincent O. Boer3, Ane Kloster1,2, Martin Prener1,2, Helle Juhl Simonsen6, Olaf B. Paulson1,2, Lars H. Pinborg1,2, and Melanie Ganz1,7
1Neurobiology Research Unit, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark, 2Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark, 3Danish Research Centre for Magnetic Resonance, Funktions- og Billeddiagnostisk Enhed, Copenhagen University Hospital Hvidovre, Copenhagen, Denmark, 4Dept. of Health Technology, Technical University of Denmark, Kongens Lyngby, Denmark, 5Philips Healthcare, Copenhagen, Denmark, 6Functional Imaging Unit, Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet Glostrup, Copenhagen, Denmark, 7Dept. of Computer Science, University of Copenhagen, Copenhagen, Denmark

Automated cortical segmentations benefit from higher SNR and spatial resolutions on 7T MR images, but are also challenged by B1 inhomogeneities, causing faulty surface inflations primarily in the temporal lobes. We investigated how FreeSurfer outputs were affected by applying eight different preprocessing schemes prior to reconstructions of submillimeter 7T MPRAGE images. The highest segmentation robustness across subjects was obtained by setting bias-field correction FWHM to 60mm and adding light regularization, and additionally performing intensity normalization.

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