Effect of limited segmentation performance on regional qMRI parameter estimations using FSL FIRST in anatomical regions with poor T1 contrast
Fahad Salman1, Niels Bergsland1,2, Michael Dwyer1,3, Bianca Weinstock-Guttman4, Robert Zivadinov1,3, and Ferdinand Schweser1,3
1Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences at the University at Buffalo, Buffalo, NY, United States, 2IRCCS, Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy, 3Center for Biomedical Imaging, Clinical and Translational Science Institute, The State University of New York, Buffalo, NY, United States, 4Jacobs Multiple Sclerosis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, United States
Most T1w imaging sequences produce only weak deep gray matter (DGM) contrast compared to iron-sensitive techniques such as QSM. In particular, using multi-modal information in both template generation and brain normalization steps has the potential to result in improved segmentation performance. In this study, we compared FIRST to a custom multi-contrast T1w-QSM atlas segmentation approach for estimating thalamic volumes and susceptibility. Our study suggested that an advanced atlas-based approach may result in better regional segmentations of regions with weak T1w contrast and result in more accurate parameter estimates.
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