  Recent progress in tissue clearing has allowed for the imaging of entire
organs at single-cell resolution. These methods produce very large 3D images
(several gigabytes for a whole mouse brain). A necessary step in analysing
these images is registration across samples. Existing methods of registration
were developed for lower resolution image modalities (e.g. MRI) and it is
unclear whether their performance and accuracy is satisfactory at this larger
scale. In this study, we used data from different mouse brains cleared with the
CUBIC protocol to evaluate five freely available image registration tools. We
used several performance metrics to assess accuracy, and completion time as a
measure of efficiency. The results of this evaluation suggest that the ANTS
registration tool provides the best registration accuracy while Elastix has the
highest computational efficiency among the methods with an acceptable accuracy.
The results also highlight the need to develop new registration methods
optimised for these high-resolution 3D images.

Computer Vision and Pattern Recognition