Abstract
Functional ultrasound imaging (fUSI) is an emerging hemodynamic-based neuroimaging technique that combines high spatiotemporal resolution and sensitivity with extensive brain coverage, enabling a wide range of applications in preclinical brain research. Based on power Doppler imaging, fUSI measures changes in cerebral blood volume by detecting the back-scattered echoes from red blood cells moving within its field of view. Despite the significant contribution of fUSI technology to neuroscience research, its full potential is partly constrained by the challenge of accurately co-registering power Doppler vascular maps acquired across different sessions and/or animals to a single reference: an approach that could widen the scope of experimental paradigms and enable the utilization of advanced data analysis tools. This study aims to address this critical limitation by comparing eight image registration techniques to align 2D sagittal whole-brain fUSI datasets acquired from 82 anesthetized mice. The results showed a significant improvement in the alignment of fUSI images across all techniques. However, the non-rigid registration methods demonstrated either similar or superior performance in similarity metrics compared to rigid approaches, with the non-rigid version ofElastixandImregdeformemerging as the top-performing techniques. Further analysis revealed that both methods maintained comparable high levels of geometric integrity, as evidenced by similar mean Jacobian determinants (close to 1) and low folding rates. In summary, our study offers the first comparative analysis of image registration techniques specifically tailored for 2D fUSI mouse brain datasets, paving the groundwork for enhanced utilization of fUSI in future research applications.