Multi-channel registration for diffusion mri: longitudinal analysis for the neonatal brain

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Abstract

In multi-channel (MC) registration, fusion of structural and diffusion brain MRI provides information on both cortex and white matter (WM) structures thus decreasing the uncertainty of deformation fields. However, the existing solutions employ only diffusion tensor imaging (DTI) derived metrics which are limited by inconsistencies in fiber-crossing regions. In this work, we extend the pipeline for registration of multi-shell high angular resolution diffusion imaging (HARDI) [15] with a novel similarity metric based on angular correlation and an option for multi-channel registration that allows incorporation of structural MRI. The contributions of channels to the displacement field are weighted with spatially varying certainty maps. The implementation is based on MRtrix3 (MRtrix3: https://www.mrtrix.org) toolbox. The approach is quantitatively evaluated on intra-patient longitudinal registration of diffusion MRI datasets of 20 preterm neonates with 7–11 weeks gap between the scans. In addition, we present an example of an MC template generated using the proposed method.

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Uus, A., Pietsch, M., Grigorescu, I., Christiaens, D., Tournier, J. D., Grande, L. C., … Deprez, M. (2020). Multi-channel registration for diffusion mri: longitudinal analysis for the neonatal brain. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12120 LNCS, pp. 111–121). Springer. https://doi.org/10.1007/978-3-030-50120-4_11

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