Recommendations for registration troubleshooting

When first attemting preprocessing with RABIES, we recommend following the default parameters as they involve less stringent modifications of the images and mostly rely on the original quality of the MR images at acquisition. However, the default parameters do not offer a generalizable robust workflow for every datasets, and to reach ideal outcomes, the workflow parameters may require tuning. We provide below recommendations for common types of registration failures that may be found from the QC report.

Inhomogeneity correction (anat or BOLD) --anat_inho_cor, --bold_inho_cor, --anat_robust_inho_cor, --bold_robust_inho_cor

• Only a subset of the scans have failed masking, or the mask is partially misregistered: Consider using the --anat_robust_inho_cor/--bold_robust_inho_cor option, which will register all corrected images to generate a temporary template representing the average of all scans, and this template is then itself masked, and becomes the new target for masking during a second iteration of inhomogeneity correction. This should provide a more robust registration target for masking. The parameters for handling this setp are the same as --commonspace_reg below.

• The inhomogeneity biases are not completely corrected: if you observe that drops in signal are still present after the connection, you should consider applying multiotsu=true. This option will better correct low intensities in an image with important signal drops.

• Tissue outside the brain is provoking registration failures: if the intensity of tissue outside the brain was enhanced during the initial inhomogeneity correction and leads to masking failures, you can consider using --anat_autobox/--bold_autobox which can automatically crop out extra tissue. You can also modify the otsu_thresh to set the threshold for the automatic masking during the initial correction, and attempt to select a threshold that is more specific to the brain tissue.

• There are still a large proportion of masking failures (mismatched brain sizes or non-linear wraps, or mask outside of the brain): Consider applying a less stringent registration method, going down from SyN -> Affine -> Rigid -> no_reg . If no_reg is selected, you may have to also adjust the otsu_thresh to obtain an automatically-generated brain mask covering only the brain tissues.

Commonspace registration --commonspace_reg or susceptibility distortion correction --bold2anat_coreg

• Many scans are misregistered, or brain edges are not well-matched: First, inspect the quality of inhomogeneity correction for those scans, and refer to instructions above if the correction or brain masking was poor. If good quality masks were obtained during inhomogeneity correction, they can be used to improve registration quality by using masking=true. If registration errors persist, in particular if brain edges are not well-matched, brain_extraction=true can be used to further constrain the matching of brain edges after removing tissue outside the brain. However, the quality of brain edge delineation depends on masks derived during inhomogeneity correction, so this option depends on high quality masking during this previous step.

• Scans have incomplete brain coverage (e.g. cerebellum/olfactory bulbs), and surrounding brain tissue is streched to fill in missing regions: The non-linear registration assumes corresponding brain anatomy between the moving image and the target. If brain regions are missing, the surrounding tissue may be improperly stretched to fill missing areas. Using the brain_extraction=true can largely mitigate this issue.