PT  - JOURNAL ARTICLE
AU  - Pei Huang
AU  - Johan D. Carlin
AU  - Richard N. Henson
AU  - Marta M. Correia
TI  - Improved motion correction of submillimetre 7T fMRI time series with boundary-based registration (BBR)
AID  - 10.1101/747386
DP  - 2019 Jan 01
TA  - bioRxiv
PG  - 747386
4099  - http://biorxiv.org/content/early/2019/08/28/747386.short
4100  - http://biorxiv.org/content/early/2019/08/28/747386.full
AB  - Ultra-high field functional magnetic resonance imaging (fMRI) has allowed us to acquire images with submillimetre voxels. However, in order to interpret the data clearly, we need to accurately correct head motion and the resultant distortions. Here, we present a novel application of Boundary Based Registration (BBR) to realign functional Magnetic Resonance Imaging (fMRI) data and evaluate its effectiveness on a set of 7T submillimetre data, as well as millimetre 3T data for comparison. BBR utilizes the boundary information from high contrast present in structural data to drive registration of functional data to the structural data. In our application, we realign each functional volume individually to the structural data, effectively realigning them to each other. In addition, this realignment method removes the need for a secondary aligning of functional data to structural data for purposes such as laminar segmentation or registration to data from other scanners. We demonstrate that BBR realignment outperforms standard realignment methods across a variety of data analysis methods. Further analysis shows that this benefit is an inherent property of the BBR cost function and not due to the difference in target volume. Our results show that BBR realignment is able to accurately correct head motion in 7T data and can be utilized in preprocessing pipelines to improve the quality of 7T data.