Comparison of image registration techniques in functional ultrasound imaging

Abstract

Functional Ultrasound Imaging (fUSI) is an emerging hemodynamic-based functional neuroimaging technique that combines high spatiotemporal resolution and sensitivity, as well as extensive brain coverage, enabling a range of applications in both control and disease animal models. Based on power Doppler (pD) imaging, fUSI measures changes in cerebral blood volume (CBV) by detecting the back-scattered echoes from red blood cells moving within its field of view (FOV). However, the expansion of fUSI technology is partly limited by the challenge to co-register pD vascular maps acquired across different sessions or animals to one reference; an approach that could widen the scope of experimental paradigms and enable advanced data analysis tools. In this study, we seek to address this critical limitation. We evaluate six image registration techniques, predominantly used in other neuroimaging studies, using 2D sagittal whole-brain fUSI data from 82 anesthetized mice, and tested the quality of registration using multiple metrics. Our findings indicate a substantial enhancement in the alignment of fUSI images post registration. Among the tested techniques, the non-rigid registration algorithm Imregdeform yielded superior performance. We offer the first comparative study of image registration techniques for a 2D fUSI brain dataset, paving a way for improved utilization of fUSI in future pre-clinical research applications.