Abstract #3667

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

Giske Opheim^1,2, Oula Puonti^3,4, Jan Ole Pedersen⁵, Vincent O. Boer³, Ane Kloster^1,2, Martin Prener^1,2, Helle Juhl Simonsen⁶, Olaf B. Paulson^1,2, Lars H. Pinborg^1,2, and Melanie Ganz^1,7

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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